Material Flow Cost Accounting application and its ... · Material Flow Cost Accounting application...

Material Flow Cost Accounting application and its

Integration with Lean Tools

Helena Craveiro Patrocínio Cecílio

Thesis to obtain the Master of Science Degree in

Mechanical Engineering

Supervisor: Prof. Paulo Miguel Nogueira Peças

Examination Committee

Chairperson: Prof. Rui Manuel dos Santos Oliveira Baptista

Supervisor: Prof. Paulo Miguel Nogueira Peças

Members of the Committee: Profª. Elsa Maria Pires Henriques

Profª. Inês Esteves Ribeiro

November 2017

iii

Acknowledgements

First of all, I would like to express my deep gratitude to my supervisor, Prof. Paulo Peças . His expertise,

guidance, support and motivation, which were crucial to achieving my goals on this important project in

my life. Moreover, I would like to thank him for being always available to share his knowledge with

patience and kindness.

Special thanks to Prof. Uwe Götze and Dr. Rooney Sygulla for share their knowledge, for the availability

and the support during this work development.

I would also like to thanks to the company that welcomed me and allowed the development of my work

which is now completed. Their kindness and support were fundamental for this work. I would like to

express my sincere thanks to Dr. Miguel for his guidance and Sara for the amazing integration process

and for all the support inside the company. I would also like to thanks, to Hugo, Isabel, Joana, Gil, and

all the employees which stops their jobs to support mine.

To my university friends, for always supported me. Especially to Patricia Paiva my favourite Spanish girl

for her friendship and her inexhaustible support shared since the first day we met. To Mary, my almost

twin for all the patience, the support and help during this long journey that is our friendship. To Vivi, for

all the friendship and the amazing talks that makes me fell away of my problems. Thanks to António for

always making me laugh, for all the support and the patience. Also, to my high school friends, Soraia,

Marina, Sara, Camarão, Edu for the availability, help and support during all these years.

I would like to thank my parents from the bottom of my heart, for the unconditional love, for all the

patience, for all support, for always encouraged me to take risks and face the challenges. Thanks for

the ERASMUS opportunity, thanks for always believing in me and the most important thing, thanks for

showing me the real meaning of the word “Familia” (family).

To my sister Joana, for always believing in me and for being the best example that a could ever have.

To my brother João, for always think positive, encourage me to draw my own journey, for never leave

me alone, for always believed in my potential. To my aunts and cousins, and especially to my

grandmothers who unfortunately are looking at me from the heaven but always encouraged me to follow

my dreams.

Last, but not least, I would like to thank João Nuno, for always support me, for always encourage me to

overcome my fears and never allowed me to give up.

“Who walks alone might even get faster,

but one that is accompanied surely goes further”.

Clarice Lispector

iv

Resumo

Com a emergente necessidade das empresas se tornarem mais competitivas, industrias relacionadas

com a manufatura de componentes tendem cada vez mais a procurar soluções simples e eficazes que

lhes permitam aumentar a produtividade mantendo ou diminuindo o custo inerente. No entanto, no

decorrer das últimas décadas a consciencialização social sobre problemas ambientais tem vindo a

aumentar. Quando confrontadas com esta realidade estas empresas, sentiram necessidade de

procurar soluções que possibilitassem a redução do impacto ambiental das suas atividades a par da

componente económica focando-se essencialmente no controlo e redução de custos associados.

A presente dissertação foca-se na análise da viabilidade da aplicação do Material Flow Cost Accounting

como uma ferramenta de diagnóstico e na integração do Material Flow Cost Accounting com

ferramentas de gestão de produção para eliminação de desperdícios (Lean tools). Esta integração é

possível devido ao fato de tanto o MFCA como as Ferramentas Lean terem como objetivo principal a

eliminação de desperdícios.

Com propósito de se atingir os objetivos acima expostos, o MFCA é primeiramente aplicado a uma

unidade de produção de injeção de moldes. Esta aplicação possibilita o reconhecimento das vantagens

e limitações deste método. Quando associada a uma observação detalhada do processo permite o

reconhecimento de ineficiências inerentes a este que o MFCA por si só não tem capacidade de

reconhecer. Posteriormente é elaborada uma revisão bibliográfica sobre os possíveis aspetos

complementares dos métodos acima mencionados. Tendo por base esses factos uma metodologia de

integração é apresentada e primeiramente validada com a sua aplicação a um caso prático.

Em suma, o estudo apresentado permitiu o desenvolvimento de uma proposta de metodologia de

integração do MFCA com as ferramentas Lean. Esta nova metodologia possibilita a alteração do

sistema produtivo de maneira a que estes componentes sejam produzidos de forma mais ecológica e

com menor nível de desperdícios. Esta metodologia é aplicada como um ciclo de melhoria continua

tendo como objetivo a evolução do processo de produção aproximando-se cada vez mais do ideal.

Palavras-Chave: Material Flow Cost Accounting, Lean tools, Gestão de Produção, Processo de

Injecção de Moldes, Melhoria Continua.

v

Abstract

With the emergent need for companies to become more competitive, industries related with manufacture

of components tend to search for simple and effective solutions which allow them to increase productivity

while maintaining or decreasing the cost involved. However, during the last decades the social

awareness about environmental problems has been increasing. When faced with this reality, companies

felt the need to seek solutions that enable the reduction of the environmental impact of their activities

alongside with the economic component focusing mainly on control and reduction of associated costs.

This dissertation focuses in the analysis of the application of Material Flow Cost Accounting as a

diagnostic tool and its integration with production management tools for waste elimination, particularly

Lean tools. This hypothesis is possible due to that both MFCA and Lean tools has as main goal the

waste elimination.

To achieve the objectives previously stated, the MFCA is primary applied to a production unit of mould

injection. This application allows the recognition of the advantages and limitations of this method. When

associated with a detailed process observation it allows to recognise inefficiencies that the MFCA alone

has no capability to identify. Thereafter, a literature review is performed to assess the complementary

aspects of both, MFCA and Lean tools, methods. In order to validate the developed methodology a

case-study was used.

Concluding, the study presented allowed the development of a methodology integrating MFCA and Lean

tools. This novel methodology allows the change in the production system enabling an environmental

friendly and a low-level waste production of components. The methodology when implemented acts like

a continuous improvement cycle so the production process moves closer to the ideal optimized process.

Key-Words: Material Flow Cost Accounting, Lean manufacturing, Production Management

Continuous improvement, Injection Moulding Process.

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Contents

Acknowledgements .............................................................................................................................. iii

Resumo.................................................................................................................................................. iv

Abstract .................................................................................................................................................. v

Contents ................................................................................................................................................ vi

List of Figures ..................................................................................................................................... viii

List of Tables ......................................................................................................................................... ix

Nomenclature and symbols ................................................................................................................. x

1. Introduction .................................................................................................................................... 1

2. Literature Review of Material Flow Cost Accounting ................................................................. 3

2.1. History and fundamentals of MFCA ...................................................................................... 3

2.1.1. Historical Development of Material Flow Cost Accounting ....................................... 3

2.1.2. Principals and Fundamentals of Material Flow Cost Accounting ............................. 4

2.2. MFCA application Methodology ............................................................................................. 6

2.2.1. Energy Flow and Energy Cost Analysis ................................................................. 10

2.2.2. Loop analysis – Recycling processes ..................................................................... 13

2.3. Material Flow and Traditional Cost Accounting ................................................................... 14

3. Company’s description and work’s approach .......................................................................... 16

3.1. The Company’s description ................................................................................................. 16

3.1.1. Production System Characterization ...................................................................... 16

3.1.2. The injection moulding machine and process ........................................................ 19

3.2. Dissertation Approach ......................................................................................................... 22

4. MFCA application in a production system which follows an MTS strategy .......................... 24

4.1. Case-Study’s Preparation.................................................................................................... 24

4.1.1. Quantity Centres determination .............................................................................. 25

4.2. Quantification of the material flows ..................................................................................... 26

4.2.1. Materials determination and classification .............................................................. 26

4.2.2. Procedure Followed to Collect Data in Physical Units ........................................... 27

4.3. Quantification Energy, System and Material Flows in monetary units ................................ 31

4.4. MFCA compilation data for the Calculation model .............................................................. 34

4.5. MFCA application results and its analysis ........................................................................... 35

4.5.1. MFCA results .......................................................................................................... 35

vii

4.5.1. Complementary analysis based on MFCA results ................................................. 37

4.6. MFCA application conclusions............................................................................................. 41

5. Methodology for MFCA and Lean Tools Integration ................................................................ 43

5.1. MFCA and Lean approaches ............................................................................................... 44

5.2. MFCA-Lean Methodology.................................................................................................... 49

5.2.1. Objectives and Scope Definition ............................................................................. 51

5.2.2. Operational KPIs definition ..................................................................................... 51

5.2.3. MFCA application and KPIs calculation .................................................................. 52

5.2.4. Process mapping: KPIs vs Target Values .............................................................. 54

5.2.5. Critical QC and KPIs identification and Lean tools application............................... 55

5.3. MFCA-Lean Methodology application ................................................................................. 55

5.3.1. Production system and product characterisation ................................................... 56

5.3.2. Objectives, Scope and Operational KPIs Definition ............................................... 56

5.3.1. MFCA application and data gathering .................................................................... 57

5.3.2. Energy, System and Material cost calculation ........................................................ 59

5.3.3. Calculation model ................................................................................................... 61

5.3.3.1. KPI calculation ........................................................................................................ 62

5.3.3.1.1. KPI selection and calculation for QC ................................................................. 62

5.3.3.1.2. KPI selection and calculation for Total Production System ............................... 63

5.3.3.1.3. KPIs vs Target Values ....................................................................................... 63

5.3.4. Critical QC and KPIs identification .......................................................................... 64

5.3.5. Lean application tools ............................................................................................. 68

5.3.5.1. Lean Root-Cause tools application ......................................................................... 68

5.3.5.2. Lean problem-solving solutions application ............................................................ 72

5.4. Methodology application conclusions .................................................................................. 74

6. Conclusions ................................................................................................................................. 75

7. Future Work .................................................................................................................................. 76

8. References .................................................................................................................................... 77

9. Annexes ........................................................................................................................................... I

Annex A - Equipment identification ................................................................................................... I

Annex B - Company’s Teams and departments ............................................................................. III

Annex C - Operating materials – QC and utilisation ....................................................................... IV

Annex D - Employees’ time distribution per QC .............................................................................. V

Annex E – Analysis to reduce the number of mouldings rejected after stops ............................... VII

viii

List of Figures

Figure 2-1 – MFCA – Flow model example adopted from [3], [13] ......................................................... 5

Figure 2-2 Plan-Do-Check-Act cycle for MFCA implementation adapted from [3], [15] .......................... 7

Figure 2-3 Departments involved in MFCA implementation .................................................................... 7

Figure 2-4 – QC general cost analysis adapted from [3] ......................................................................... 9

Figure 2-5 – Material and Energy flow map, adapted from [2], [13] ...................................................... 12

Figure 3-1 General processes description ............................................................................................ 17

Figure 3-2 Scheme of a screw injection machine [24] .......................................................................... 20

Figure 3-3- Scheme of the injection moulding process adapted from Biswajit, S et al.(2015),[25] and

injection moulding cycle [26][27] ........................................................................................................... 21

Figure 3-4 Approach followed to develop the present work. ................................................................. 23

Figure 4-1 Production of product A – Material flow map ....................................................................... 26

Figure 4-2 – Data collecting procedure ................................................................................................. 28

Figure 4-3 – Auxiliar calculation model approach ................................................................................. 29

Figure 4-4 Flow maps obtained from the MFCA calculation model ...................................................... 36

Figure 4-5 Contribution of each parameter for the QC’s product cost .................................................. 39

Figure 4-6 Contribution of each parameter for the QC’s waste cost ..................................................... 40

Figure 5-1 Sankey diagram of a production system .............................................................................. 45

Figure 5-2 - Complementary aspects and integration opportunity ........................................................ 49

Figure 5-3- Overview of the MFCA-Lean methodology ......................................................................... 51

Figure 5-4 A proposal of QC and Total Production System dashboards output data, the comparison with

Target Values and the performance indicators. ..................................................................................... 54

Figure 5-6- Material Flow model ............................................................................................................ 58

Figure 5-7 – Methodology dashboard for the production system per QC ............................................. 65

Figure 5-8 Methodology general dashboard of Total Production System ............................................. 65

Figure 5-9 Root-cause analysis to the QC-Injection Machine ............................................................... 69

Figure 5-10 Root-cause analysis to the QC-Packaging ........................................................................ 70

Figure 5-11 Root-cause analysis to the Total Production Time ............................................................. 71

Figure 5-12 Cause analysis of the critical value of the total system cost .............................................. 72

ix

List of Tables

Table 3-1 Equipment allocation based on the production strategy........................................................ 18

Table 4-1 Characteristics of the product A ............................................................................................. 24

Table 4-2 Product A- Auxiliary materials identification ........................................................................... 27

Table 4-3 Part2 QC Injection Machine ................................................................................................... 35

Table 4-4 Production cost distribution per part ...................................................................................... 37

Table 4-5 Added cost per QC and total contribution .............................................................................. 38

Table 5-1- A general description of 8 MUDA ......................................................................................... 46

Table 5-2 Lean Tools description for problem-solving ........................................................................... 46

Table 5-3 Lean Tools description for root cause identification ............................................................... 47

Table 5-4 Lean Tools description for good practices ............................................................................. 48

Table 5-5- KPI recommended for the integration approach and its application .................................... 51

Table 5-6 – General dimensions of the production process and product .............................................. 56

Table 5-7 – Key Performance Indicators to evaluate the performance considering the company’s goals.

............................................................................................................................................................... 57

Table 5-8- Percentage distribution of employees per QC. .................................................................... 59

Table 5-9- QC-Injection Machine ........................................................................................................... 61

Table 5-10 Identification of critical QC and KPI (per QC and TPS) ....................................................... 66

Table 5-11 The contribution of each QC-System within the Total System Cost .................................... 67

Table 5-12 Comparison value between System cost of Packaging and Injection Machine processes. 68

Table 5-13 Setup time after lean tools application ................................................................................ 73

Table 5-14 Final Results after Lean application tools ............................................................................ 74

Table B-9-1-Teams and departments involved in the manufacturing process ....................................... III

x

Nomenclature and symbols

Variation

ECA Energy Cost Accounting

EMS Environmental Management System

FP Final Product

IM Injection Machine

KPI(s) Key Performance Indicator(s)

MEFCA Material and Energy Flow Cost Accounting

MFCA Material Flow Cost Accounting

MTO Make-To-Order

MTS Make-To-Stock

PDCA Plan-Do-Check-Act

PP Polypropylene

QC Quantity Centre

SMED Single Minute Exchange of Dies

TPS Total Production System

TV Target Value

WM Waste Management

1

1. Introduction

Nowadays, a modern, competitive and environmental concerned society are pressuring companies to

achieve higher productivities with the lowest possible environmental impact [1]. Thus, few alternative

methods have been emerging, to support management decisions in terms of economic performances

and simultaneously consider the environmental impact and production volumes[1], [2]. Under current

circumstances, Material Flow Cost Accounting (MFCA) is considered one of the main tools for

Environmental Management Accounting (EMA). Consequently, MFCA is one of the methods that are

considered an approach which can contribute to pacify the society’s pressure since it allows the harmony

between sustainability and profitability [1].

Material Flow Cost Accounting, according to ISO standard 14051[3], is a management tool which fosters

the transparency of energy and material flows and consumptions. This method has been developed to

support industrial companies on material and energy efficiency and to support management decisions

by presenting the effective value of the company’s waste. Assuming that the economic impact is one of

the most important factors in the company’s environment, MFCA results should motivate managers to

re-consider their strategy in order to increase production efficiency[4].

Lean Management is also recognised as a solution for waste elimination. Its main goal is the

identification and elimination of several types of waste allowing companies to achieve an efficient

customer demand. Furthermore, Lean Management domain is mainly related with physical flows and

do not directly consider, the economic impact of its improvements. It aims to eliminate all types of waste

directly on the manufacturing system by incremental changes working as continuous improvement cycle

[5].

In one hand, MFCA aims to inform the managers of the real waste value and the sub-division processes

in which the product or component had an increased value or a considerable waste cost. On the other

hand, Lean Management tools goals are directly related with physical flow analyses and problem-solving

solutions. Due to the MFCA and Lean tools complementary aspects, arises the hypothesis of integrate

both.

Firstly, MFCA methodology is applied to a Plastic injection moulding system in a Portuguese company.

Then, to support the hypothesis of integration, the MFCA and Lean management complementarities and

gaps are primarily observed to identify improvement opportunities in manufacturing domain during the

MFCA application. Further, to support the hypothesis of integrate MFCA and Lean tools, their

complementarities aspects and gaps of knowledge are studied based on scientific literature. Thereafter,

a methodology to integrate MFCA and Lean management, is presented and preliminarily validated with

a case study.

The present dissertation begins with a literature review about Material Flow Cost Accounting, including

its historical development, its objectives, principles and fundamentals, as well as the methodology

proposed for MFCA application, presented in Chapter 2.

2

The main goals of this work and the approach followed is described and presented in Chapter 3, as well

as the company’s description, the characterization of the production system used as case-study.

Moreover, the Injection moulding process, machine and its variables are also briefly described in this

Chapter.

Chapter 4 presents the methodology followed for the application of the MFCA, as well as the product

characteristics and type of production system. Moreover, the calculation model developed for the

diagnosis analysis of the production system is described. Further, the diagnosis of the case-study

production process is performed and the obtained results are presented and analysed. At the end of

Chapter 4, the inefficiencies existent in the production system are presented, discussed and some

improvement solutions are suggested.

In Chapter 5, firstly, a conceptual review related with MFCA and Lean manufacturing tools focusing on

their complementarities is presented. Then, the methodology for integration is organised by presenting

its steps and the final output – MFCA and Lean related KPIs dashboards. Further, the methodology is

applied to a case study developed in an injection moulding production system, including also the

improvement solutions elaborated. This application aims to preliminary validate the presented

methodology. The chapter ends with conclusions about the potential of the presented methodology

based on the results achieved by its application.

Finally, the conclusions and future work are presented.

3

2. Literature Review of Material Flow Cost

Accounting

The growing concerned about climate change and material scarcity since the 80’s have been pressuring

companies to perform their activities with the lowest environmental impact possible[6]. Moreover, the

necessity of meeting the requirements imposed about resources consumption and emissions are forcing

companies to improve its practices in this subject. Nevertheless, companies need to remain competitive

in a worldwide market, achieving higher productivity levels[7], [8]. In consequence, managers are facing

the challenge of integrating ecological goals with economic objectives [8]. To answer those requirements

Material Flow Cost Accounting (MFCA) has been suggested by several authors as one of those tools

that can support companies in decision making for economic and environmental improvements [1].

In this context, MFCA is considered a promising approach since it is recognised as a specialised

accounting method and one of the principal tools of Environmental Management Accounting[3], [8].

MFCA presents the comparison costs between positive products (product) and negative products

(waste), allowing the enhancement of material and energy uses efficiency. Once, the cost of waste is

visible it can drive managers to re-plan their strategy. As soon as this strategy is implemented the

resources reduction can be achieved and consequently a reduction of the overall production cost and

environmental impact can be accomplished [4].

The present Chapter is organised as follow. Firstly, a history development of MFCA is presented as well

as its objective, scope, principals and fundamentals. Then the implementation methodology based on

ISO standard 14051[3] is described. Thereafter, a brief discussion between traditional cost accounting

and Material flow cost accounting is presented to provide a better understanding about MFCA

implementation advantages.

2.1. History and fundamentals of MFCA

2.1.1. Historical Development of Material Flow Cost Accounting

The first, and primary, concept of MFCA is the mass balance. It is based on the laws of thermodynamics,

which postulates that the material or the energy in any system cannot be created or destroyed, it can

only be transformed. This, translated to a company’s reality, means that the resources that enter in the

systems of the company, will leave it in the exact same amount, in the form of product or waste; or

increasing the existing stock [6].

The MFCA appears to face the environmental issues, and its subsequent protection measures, which

began to appear in the 80’s. Thus, the MFCA arises from an environmental management project in a

textile company in Southern Germany named Kunert at the end of the 80’s[6]. Though, the original

4

concept of the MFCA was developed in the late 90’s at ‘Institut für Management und Umwelt', Germany.

Posterior few pilot projects were initialised in the German industry. Nevertheless, the first breakthrough

of MFCA was accomplished in Japan. Due to the successful results of the first implementations, the

‘Japanese Ministry of Economy, Trade and Industry’, in 2000’s, encouraged the application of the

methodology in more than three hundred Japanese companies. The achieved results lead these

companies to apply the MFCA methodology since then [9]–[11].

Simultaneously, to support the companies on the MFCA application field, the ISO 14000 was developed

in 2007 in Japan. Its primary objective was to standardise the general concept and its framework, for

the application of the methodology in small and medium companies [9]. The methodology was then

improved, and the final version was published in September 2011, as ISO14051 [10], [12].

The MFCA was firstly designed for single processes and organisations. However, it can be extended to

a supply chain, and there are some successful examples of it. Nevertheless, it requires the sharing of

confidential information between all the companies. To overcome the possible issues and lacks, as well

as to support the companies in its application, a new ISO has been developed since 2014, ISO 14052

[10].

2.1.2. Principals and Fundamentals of Material Flow Cost

Accounting

The MFCA is considered as one of the most powerful tools of Environmental management Accounting.

It is also an effective approach to meet the necessity of increase the productivity and reduce the

environmental impact at the same time, through the promotion of the transparency of material and

resources use[3].

The MFCA is characterized for being a flow orientated accounting method that traces and quantifies in

physical and monetary units all the material and energy flows. Furthermore, it compares the costs

associated to the products and the material losses[1]. The applicability of this method is independent of

the type of production system or organization. Its only requirement is that the company uses material

and energy for its activity [3].

The MFCA method divides the entire production system into Quantity Centres (QC). The QCs are parts

or sub-divisions of the manufacturing system where the inputs and outputs must be quantified in physical

and further in monetary units. Usually, these areas corresponds to places where materials are

transformed, or stocked [3],[9]. The QC is the starting point for data collection in physical units in terms

of resources measurements.

For each QC the material and energy used must be measured in physical units. Then, all the information

related to the QCs must be compiled in a flow model. The flow model (Figure 2-1) illustrates the materials

and the energy flows, as inputs and outputs of the QC. It is important to note that the output flows are

sub-divided into material and waste, based on an allocation rule previously selected [3], [13].

5

Figure 2-1 – MFCA – Flow model example adopted from [3], [13]

The final flow model of the production system, Figure 2-1, must provide an overview of process in

analysis [3]. Further, this flow map allows the identification of points where the material and energy

waste can occur based on its costs. That, should motivate managers and engineers to re-organize their

strategy or re-plan this QC performance [9], [14].

The base concept of the MFCA, as it was referred, is the conservation law of material and energy.

Considering this principle, and to guarantee that all the flows are accounted, a mass balance should be

performed to the production system per QC individually. The mass balance must consider the material

inputs, the outputs (product and waste), and the inventory stocks fluctuations. This validation is an

essential requirement for the MFCA analysis and is calculated using Equation (2.1) [1], [3].

𝐼𝑛𝑝𝑢𝑡𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙 = 𝑂𝑢𝑡𝑝𝑢𝑡𝑝𝑟𝑜𝑑𝑢𝑐𝑡 + 𝑂𝑢𝑡𝑝𝑢𝑡𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙 𝑤𝑎𝑠𝑡𝑒 + ∆ 𝐼𝑛𝑣𝑒𝑛𝑡𝑜𝑟𝑦 (2.1)

Nevertheless, some inaccuracies can occur due to some difficulties in the accounting of material which

are not easily quantified probably related to intake of moisture or air, or chemical reactions, among

others. The unexplained irregularities must be further analysed and investigated to appraise its impact

[3].

MFCA considers the production of goods as a system of material’s flow, as can be predicted from

Equation (2.1). MFCA distinguish the movements of materials in [9]:

1. Desired material flow – Movement of material that intend to become part of the final product;

2. Undesired material flow – movement of unintended materials output.

The MFCA point as undesired material flows the flows resultant of [3], [15]:

1. Operating materials as cleaning solvents, chemical catalysts, detergents, lubricants;

2. Material losses during production system and defective products;

3. Material losses due to destructive control tests;

6

4. Materials (usually raw material) in Work-In-Process and stock of rejected products due to

deterioration or off-specifications components;

5. Operating materials remaining in the equipment after set-up or maintenance activities that

will not became part of the final product.

For the MFCA point of view there is no sub-process excluded of being a source of loss before it is

subjected to an evaluation, especially when the analysis field is the manufacturing industry[15]. This

extensive search for inefficiencies and sources of waste may lead to the development of action plans to

decrease undesired outputs. The decrease of unwanted outputs entails the reduction of input materials,

influences positively the economic and ecological effects and increases productivity of the company and

its competitive capacity[9].

To conclude, the MFCA describes and evaluates the flow of materials and energy, aiming at the

improvement of the resources. The identification of the sources of waste may lead to its reduction or

elimination, contributing to reduce the demanded resources, as well as the environmental impact and

the production costs [9], [16].

Additionally, the MFCA application and implementation requires an extensive and precise data collection

which may create the opportunity of improving the existing accounting system of the company.

Moreover, it can also provide the required information for future projects [9].

2.2. MFCA application Methodology

The application of the MFCA in an organization, independently of its production field, requires the

implementation of several steps which need the collaboration of multiple departments [15]. Moreover,

the level of detail and complexity of the analysis is dependent of several factors, such as the organization

size, the manufacturing process and the available information. This method can be implemented in

organizations with or without Environmental Management System (EMS). Nevertheless, the

implementation process is facilitated in companies which already have an EMS [3].

The MFCA application method must be considered as a step by step procedure from the knowledge

about the method and its concept, pass through the recognition of the MFCA necessity for the company

and its implementation to evaluate the production system performance [15]. Moreover, decision-making

in companies are typically associated with economic considerations. Regarding that, the MFCA can

support this point by calculating the financial impact of wastes and becoming a useful tool for decision-

making.

If the company already has an EMS, the MFCA PDCA cycle can be included at different stages of the

EMS PDCA cycle. Furthermore, the advantages of the MFCA application will increase if it is constructed

in concordance with a PDCA cycle. Figure 2-2 illustrates an outline of the MFCA implementation steps

together with PDCA cycle in an industrial environment [3].

7

Figure 2-2 Plan-Do-Check-Act cycle for MFCA implementation adapted from [3], [15]

MFCA Plan phase

Firstly, the management level personnel should understand the practicability, advantages and value of

the MFCA. The MFCA application effectiveness is strongly dependent of its management support level

[3].

Secondly, the necessary expertise should be determined. The MFCA requires a deep knowledge of the

method and the collaboration of multiple departments as quality, logistic and engineering. (Figure 2-3)

[3].

Figure 2-3 Departments involved in MFCA implementation

Then, the boundary and the time period of analysis should be determined [3], [13]. The scope of analysis

can include a single or multiple process, an entire facility or even a supply chain. Nevertheless, in a first

approach it is recommended the selection of a single process, processes or products with a potential

significant economic and environmental impact within the organization [3], [15].

8

Once determined the boundary, the time period of data collection must be determined. This period

should be sufficiently long to consider any significant variation in the process allowing the compilation

of meaningful data. Depending on the production process selected for the analysis, the appropriate

period can be the time needed for a batch of production, a month, one-third of a year, a half-year or

even a year[3] .

Subsequently, the QCs must be carefully selected and defined [3]. The QCs are theoretical units of

MFCA calculation: if the QC are selected too roughly some relevant information about material losses’

location and negative products’ costs may become unclear; reversely, if the QCs are established too

precisely, the MFCA data compilation may be too complex and difficult [15]. Therefore, before

proceeding to the MFCA’s next phase a macro analysis of the system is recommended to assess the

authentication of the defined QC [15].

MFCA Do phase

Firstly, the inputs and outputs of each QC must be identified. Typically, the inputs are raw materials,

operating materials and energy, and the outputs are products, material and energy losses. The energy

and energy loss identification can be estimated separately or included under the material and material

loss, depending of the companies preferences [3].

Secondly, the identified input and output flows of each QC should be used to interconnect all the quantity

centres within the MFCA boundary of analysis in order to achieve a clear characterization of the

production system flow. Thereafter, each input and output should be quantified in physical units. It is

important to note that to perform the mass balance (Equation (2.1) the quantification of the flows must

be convertible into a single standardized unit. Moreover, the inventory changes cannot be omitted from

the balance and should also be quantified in the same standardised unit as well as all the materials

within the MFCA boundary[3]. The MFCA requires the quantification of all the involved materials in the

production process; however, some materials that represents a minimal environmental or economical

contribution can be neglected[3], [15].

The MFCA analysis allows the visualization and quantification of material losses to support management

decision-making. This purpose is achieved by the improvement of transparency of material losses in

physical and in monetary units [2]. Consequently, the next step of the MFCA application is the

conversion of the physical quantification into monetary[3], [15].

The output flows, of positive products and negative products (waste), do not consider exclusively the

material’s cost (Figure 2-4). Since, any production process requires several types of inputs, the analysis

should consider all the costs involved on it. Consequently, the named flow cost which have to be

assigned to the material’s flow (physical units) include all costs which can be related or are cause by

the material flow [2], [3], [15]. MFCA method divides the several types of cost into:

• Material Cost – Costs of main materials, operating or auxiliary materials. The cost of these

materials is calculated by the multiplication of the physical quantity of the specific material

9

by the cost per physical unit of this material during the collecting period [2], [3]. The use of

fixed prices allows a consistent evaluation for all the steps [3].

• Energy Cost – Cost of the energy consumed in each quantity centre. The recommended

procedure to calculate this cost is through the measurement of the consumption, directly

from the equipment and then, multiplying it by the unit cost [2], [3]. However, when the

energy consumed in a QC is difficult to measure, the energy cost should be calculated for

the entire manufacturing process and then an appropriate criterion should be selected to

allocate this value to each QC [3].

• System Cost – Cost of ‘all expenses incurred in the course of in-house handling of the

material flows, except for material costs, energy costs, and waste management costs’ [3] as

labours, transports and depreciation. Moreover, when the system cost cannot be easily

quantified for each quantity centre, an allocation criterion must be selected [3].

• Waste Management Cost – Cost incurred during the material losses handling, as shredding

process. This specific type of costs is totally attributed to the output of material waste [3],

[15].

Figure 2-4 – QC general cost analysis adapted from [3]

The MFCA distinguishes the direct costs from the indirect costs, as other cost accounting system. The

indirect costs as, administrative costs and structure costs, must be allocated by the more appropriate

criterion. In the MFCA context, ISO standard 14051 [3] suggests a two steps procedure for the indirect

cost allocation. First, the indirect costs must be allocated to the QC that they are related to, and then, to

the outgoing flows through a suitable criterion [2], [3].

Once all the information is compiled the required allocation criterions must be defined [15]. For that, a

two steps procedure is recommended:

1. To allocate cost to different QC;

2. To allocate the internal costs of the QC to product and material waste.

According to ISO standard 14051 [3], the most appropriated allocation criterion, i.e. the one that

transmits as close as possible the reality, should be applied to each case.

As explained before, the MFCA aims to support decision-making. Usually the economical evaluations

are based on monetary units. In contrast, the environmental performance assessment is commonly

based on resources consumption. Thus, to support companies in decision’s field financial and

10

environmental aspects and data collection should be performed simultaneously to create the MFCA

calculation model. This calculation model should be developed within the company considering all the

principals and fundamentals previously exposed about the MFCA methodology. Moreover, a three steps

guide for cost calculation is provided by the ISO standard 14051 [3] and includes follow:

1. Calculation of material costs;

2. Calculation and allocation of the remaining costs;

3. Integrated presentation and analysis of cost data.

The third point, corresponds to the results obtained after the MFCA analysis and allow the identification

of the QC with the material losses that are financial or economical significant. Generally, the information

provided by the MFCA may support a large variety of decisions within a company aiming at the

improvement of resources efficiency and economic performance [3].

After the MFCA results had assisted the organization to understand the extent, implications and drivers

of materials uses and losses, the MFCA data should be reviewed to appraise the opportunity of

improving the financial and environmental performances of the system in analysis and, consequently,

of the company [3]. The MFCA calculation model may support the assessment of the future financial

benefits [3].

The improvements suggested as a result of the MFCA analysis can be divided into three main levels,

although there is no specific procedure to face the MFCA typical problems, only some suggestions which

include [15]:

• Management of manufacturing - The MFCA allows the translation of production physical

quantities into production costs, making visible the achieved results.

• Improvements in production departments- The inefficiencies indicated through the posterior

MFCA analysis, can lead to enhancements of the process design or the equipment’s

replacement. The cost estimation in the production system might be partially estimated by the

MFCA.

• Development stages of a new product- The MFCA allows the visibility of the costs impact of the

processes, being an effective tool to evaluate the improvements in cost planning phases.

The assessment of improvements within the company requires the estimation of future costs and

panned views of the process and technologies configurations which are out of MFCA analysis scope

[2]. However, ISO standard 14051 [3], refers that the MFCA can also be used for planning purposes,

although it does not specifies any procedure for cost planning [2], [3].

2.2.1. Energy Flow and Energy Cost Analysis

The MFCA methodology literature reviews generally neglects an exhaustive examination concerned

energy. According to Sygulla et al. 2011 [2], MFCA methodology must be investigated from the

theoretical point of view to appraise the impact of this practice in the overall results Moreover, the

allocation of energy costs under the material flows neglects the information about the consequences

11

and drivers of energy losses. Despite the possibility of evaluating the energy loss due to heat transfer

or vibrations, this is not easily performed and most of the time is ignored from the energy flow point of

view. The identification of energy inefficiencies requires the entire categorization of the energy uses and

the differentiation of desired and undesired energy flows. Therefore, an energy balance must also be

performed [8], [13].

In most of the cases, a representative part of the costs are related to the energy consumed during the

process. The inclusion of an energy balance and ‘transparent’ models to appraise the energy

consumption and use may support the environmental concerns, namely climate changes, and

economical problems as the increasing price of the energy [3]. Subsequently, it is expected that a

detailed analysis of the energy flows and supply may lead to environmental benefits and costs savings

[8].

The inclusion of energy flows in the MFCA methodology, requires an improvement of flow structure

modelling [2]. The traditional material flow modelling should be traced and quantified in physical units

and then, the energy flow model should be outlined. This integration of both flows will result in a refined

methodology, the Material and Energy Flow Cost Accounting (MEFCA)[13].

The improvement of the MFCA through the inclusion of the energy flow analysis might contribute to the

improvement of the energy use, and consequently to the environmental performance of the organization

[8]. According with Bierer & Götze 2012 [13], the MEFCA general procedure is based on the MFCA

steps as 1.Modelling the flow structure, 2.Quantification of the energy and material flows in physical

units, and 3.Quantification of the material and energy flows in monetary units.

During the first step Bierer & Götze 2012 [13] advise for some important considerations. Firstly, there

are two type of modelling energy. On the one hand, the energy flows can be single traced to describe

its orientation for the most common forms of energy used in industry, as compressed air or electricity.

On the other hand, for materials as gas or coal, the material loss of energy conversion should be

evaluated and if it is significant and relevant for the analysis, an appropriate analysis for modelling the

energy flows must be performed, in parallel to a material flows (note that the material in this case is the

gas or coal) [8].

Furthermore, as occurs with the flows of material, the energy flows are defined as being all the energy

transmitted between QC. Thus, the energy that leaves the QC can leave as energy (efficient energy-

product) or energy loss (energy wasted). The efficient energy is all the energy used to produce the

outgoing products (good parts, and wasted parts) [2].

The energy consumption should be measured with specific instruments. Nevertheless, in some cases

the energy output flows have to be estimated or calculated through an energy conservation balance due

to difficulties or impossibilities for the measurement [8]. As it occurs in the quantification of material

flows, an energy balance must be performed to each quantity centre [13].

After that, the costs associated with the production, from all the categories mentioned before, must be

allocated to every material and energy flow described in the flow map. Figure 2-5 presents a flow model

12

for material and energy. Moreover, the system and waste management cost, first should be assign to

the respective QC and then to the QC output flows [13].

Figure 2-5 – Material and Energy flow map, adapted from [2], [13]

As explained before, the MEFCA suggest an individual quantification of flows in physical units. However,

is suggested by MFCA that all types of materials used should be quantified in a single physical unit to

facilitate the quantification and posterior allocation cost [3]. The quantification of material and energy in

the same physical units is not possible since materials are quantified in kilograms and energy in watt-

hour. Consequently a review concerned the allocation criterions for energy and material flows becomes

mandatory [8].

In MEFCA the material and energy cost are direct flow costs, while system and waste management

costs are considered indirect costs. Bierer & Götze 2012 [13], suggests a possible solution to perform

a more detailed analysis of the costs drivers. This includes a distinction between two types of costs:

• Material-Related System Costs – Includes all the expenses incurred by the in-house handling

of material flows, excluding material costs, waste management cots, energy and energy-related

system costs.

• Energy-Related System Costs – Includes all the expenses incurred by the in-house

transformation, generation, and transmission, except of the cost delivery of purchased energies.

The Energy and material related costs can also be allocated through more simple criterions based on

amount ratios. For example, the allocation based on the energy and material cost ratios. Moreover, the

QC can be categorised per type of output (energy or material) and use the rate of that unit to allocate

the output cost of the remaining [8].

The results obtained through the application of the MFCA and energy cost support the evaluation of

alternative process with the improvement of energy-related information and allow the identification of

existent dependencies between material and energy. Moreover, it supports the enhancement of energy

13

and material resource efficiency by the exposure of the financial effect of the use of these resources [8].

The probable benefits of the improvements are totally dependent on the resources flow information and

the effort to perform the MFECA analysis [2]. It should be noted that, the MFECA application

methodology should be refined. Consequently, further investigation activities are required in this field to

enhance the informative value of Energy Cost Accounting (ECA), offering suitable solutions for energy

inefficiencies and planning methods to compare different alternatives for enhance the energy use [13].

The evaluation of both production systems performed in this dissertation, by the application of MFCA,

allocates the energy cost under the material ratio. This decision was taken based on the existent gaps

of information about energy flows. Moreover, within the total production cost the contribution of energy

cost was not representative and consequently a different decision could compromise the significance

and validity of the results.

2.2.2. Loop analysis – Recycling processes

Due to the pressure to have production processes with the lower amount of wasted material, the

companies tend to include in their production units recycling processes. This type of process is

considered as an internal loop of material from the MFCA point of view. It may suggest that this type of

practices is financial and environmental favourable due to the reduction of raw material consumption

and the dispose of materials. However, it is important to note that a material loop is required because

some waste is generated during the process. Moreover, the recycling process, leads to additional costs

[8].

The characterisation flows of systems that include a recycling process is more complex due to the

interdependency of the raw material, as an input, and the output flows. Thus, to overcome these

difficulties Götze et al. 2014 [8] suggests the three following possible solutions

1. To calculate the total costs of all the material flows – The calculation of all the expenses

incurred related to the material flows includes the calculation of the raw material which is

going to be replaced by the recycled material through the corresponding linear equation

system [8].

2. To consider only the additional costs related to the material loop – This solution aims to

facilitate the previous assessment. The exclusive consideration of the additional costs is a

consequence of the fact that the material costs of the cycle will always became a part of the

output product [8].

3. The loop cost is reported separately - This solution aims to report the cost of the loop

independently to appraise the monetary effect of the material’s use inefficiency [8].

The first two solutions assign the costs of the internal loop to the output as a cost of the final product

itself, ignoring the fact that these costs are a consequence of the treatment of undesired materials.

Those solutions may be thought as contradictory with the MFCA and MFECA. To make visible the

14

inefficiencies of the material uses it is suggested the extraction and presentation of the material loop

costs as another additional and independent cost [17].

Despite the fact that the third suggestion may conflict with the MFCA methodology, in the point that this

flow is understood as a cost without a physical unit, it evaluates the material loop flows and identifies

the financial effect of the material inefficiencies. It making visible the material waste consequences which

is the ultimate goal of the MFCA [8].

2.3. Material Flow and Traditional Cost Accounting

The MFCA is a method which was firstly designed to be applied as an evaluation tool to improving the

resources efficiency [8]. Moreover, when it is compared to the Traditional Cost Accounting (TCA) it can

be recognised as a preferable tool. It presents not only the overall accounting performance, but also

points the real value of the material wasted which is commonly assumed as a necessary product loss

by the traditional methods. Consequently, the deep comprehension of their differences can support the

MFCA implementation, presenting its benefits [3].

Considering that, usually the decisions made in companies are primarily based on economic advantages

to increase margin gains, the evaluation of the existing processes and the development of alternatives

ought to be based on their monetary values. Thus, the appraisal, usually are referred to economic

records and reports which are presented by company’s management accounting system and costs.

Traditional Cost Accounting in theory provides a large variety of approaches for cost analysis, although

it largely fails in the in resources inefficiencies identification [8].

The most evidence difference between MFCA and TCA is related to the way that material losses costs

and energy inefficiencies are treated when a process is analysed. From the TCA perspective, the cost

related with material and energy inefficiencies are allocated to the product cost without being

differentiated. TCA considers the material and energy wastes as a necessary part of the production

process [3]. The material costs related to material losses are frequently pre-defined as a standard

number. Then, the current cost of the production systems is compared with previous ones, considering

the fixed value of waste, when a variance is identified its causes are analysed. These values

discrepancy, rather reflect the material losses, it only reveals that the material used is outside the

standards. Consequently, only the ones which are beyond the standards are considered as a loss.

Moreover, the waste management cost is either included in product cost or total cost related to the

production system. All these gaps results in a misunderstanding of the real dimension of the material

losses and energy inefficiencies and its impacts in the overall production system [3].

As it was previously explained, the MFCA traces all the material flows aiming to highlight the material

losses in the processes. To accomplish that goal the material flows are traced and then are treated

separately in terms of outputs – Product cost and Waste cost. These costs include all the associated

costs to transform material in products or in waste, which include the energy cost, waste management

cost, materials cost and system cost. Therefore, they are allocated to the respective outputs through a

15

suitable criterion. The MFCA, in opposition to the TCA, emphases the costs of material losses and the

costs related to inefficiencies in each step of the process, making visible the real cost of unwanted flows

(waste flows). The recognition of the sources of material loss and the more probable source of

inefficiencies supports the companies to enhance the management accounting system, as well as to

evaluate the environmental impacts of their practices [3].

Despite the fact that the MFCA includes and fills the TCA gaps concerning the evaluation of material

losses, the information provided by its application and some objectives are connected to the traditional

methods. Both, MFCA and TCA business analysis, provide relevant information for planning and

controlling operations. They also support the communication between all the employees and the

evaluation of products. However, they use that information differently. While MFCA focus on processes,

by its evaluation in terms of desired and undesired results, aiming in the analysis of the resources

efficiency; TCA uses the information about the cost, typically, to appraise the products’ cost and evaluate

economic performance of the company [8].

Therefore, from the company’s management perspective, MFCA can be recognised as a particular part

of its cost accounting system. Literature proposes an approach to integrate MFCA in the Traditional

Cost Accounting system as a specific data supplier. The proposed integration guarantees the

comparability of the results. The analysis derived from it should be understood as a study of the same

system evaluated from different perspectives, that should contribute for the enhancement of available

information to support decision making. Moreover, is expected that the detailed information about

production process regarding energy and material flows due to the MFCA application will improve the

quality of the traditional costs assessments [8].

As mentioned in the previous chapter, the MFCA analysis requires detailed information concerning the

material and energy consumptions and flows. In turns the collection of that information require their

measurement in physical units in specific points of the production system. Moreover, it is also necessary

to evaluate those physical units and allocate the respective cost to the correct outgoings. This entire

accurate process is required for the MFCA implementation and its validity. When the integration of the

MFCA as a partial system of TCA is suggested, the benefits and the possible enhancements should be

evaluated and contrasted with the necessary effort required for the MFCA application. Finally, the

appropriate implementation strategy should consider a ration between the MFCA required effort and the

TCA final benefits [8].

For the implementation procedure is also recommended, based on several applications, the previous

identification of the critical parts and then, the development of a rough flow model. It is expected that

the MFCA first application highlights the points of inefficiencies. Successful cases from Japanese

companies shows that the MFCA analysis presents more inefficiencies and material losses than the

expected from the company’s managers [3], [15], [17]. The recognition of these issues should motivate

managers to re-plan their strategy in order to eliminate these inefficiencies which may be translated in

relevant costs savings [8].

16

3. Company’s description and work’s approach

The main objectives of the present work consist in the validation of the MFCA’s applicability as a

diagnostic tool. Then, a literary a study concerning MFCA method and the Lean tools complementarities

is performed. Subsequently, based on this study, is aims to develop and methodology to integrate MFCA

method and the Lean and primarily validated it by its application to a different case study

To achieve the dissertation goals the work was partially developed in an industrial company, enabling

the necessary data collection to perform the MFCA analysis and its calculation model. Moreover, when

the MFCA is applied and continuously followed by the person who is applying it, not only, allows an

easily identification of the inherent MFCA’s gaps, but also, enables the recognition of the

complementarity opportunities related to Production management in continuous improvement domain.

This chapter aims to introduce the productive system and the industrial framework where both case-

studies were developed. Thus, the following subsections describe the company where the work was

developed, the productive system characteristics and the manufacturing process. At the end of this

chapter, the approach followed to develop the present dissertation is described.

3.1. The Company’s description

The company, where the present work was partially developed initiated his activity in the 80’s with the

Mould manufacturing unit. Lately, at the end of the 90’s the company extended it activity adding a Plastic

Injection Moulding unit. Thus, the company’s production domain was extended from mould's design and

its manufacture up to the delivery of the finished parts.

The Injection Moulding unit produces essentially components in thermoplastic, producing a large variety

of products for a wide range of industries, as food, automotive and electronics. The unit has 36 machines

and approximately 150 employees. Additionally, to complement the customer services it has several

departments which support the production systems, as logistics, quality, maintenance, assembling and

packaging.

3.1.1. Production System Characterization

The Injection Moulding unit is divided considering the production strategy. Part of this unit is totally

allocated to Make-To-Order (MTO) and the other to Mate-To-Stock (MTS) according to the production

strategy.

The Make-to-Stock (MTS) strategy occurs when the products are manufactured based on demand

forecasts originating an inventory, however if the production system were accurately forecasted it allows

a match between production and inventory preventing extensive stocks [19]. The MTS strategy is the

one selected for the production system of the first case study.

17

The Make-to-Order (MTO) strategy occurs when the products are produced only when the customer

orders it with a pre-defined production volume, avoiding unnecessary stocks [18]. This strategy is used

as a production strategy of the second case-study.

The production system is divided in six mainly activities from the material supply to the customer delivery.

Figure 3-1 presents the activities involved and its brief description considering the sequence of events.

Figure 3-1 General processes description

To perform these activities the company is divided into three main areas, the Warehouse ɪ , the Injection

Moulding, and the Warehouse ɪɪ . Subsequently, these areas are also divided and organized as follows:

• Warehouse ɪ - It is located on the floor below the Injection Moulding and is subdivided into Raw

Material area and Shredding area. Where:

Raw Material Area – It is where the raw material required for the injection moulding process is storage

until it is needed.

• Shredding area – It is where the all the defective parts are storage and shredded to be reused

or sold lately.

• Injection Moulding – It is located on zero floor and is subdivided into Production, Quality,

Packaging, Folder’s Warehouse, Mould’s Warehouse and Discharges zone:

• Production – It is the zone where the injection moulding machines are located and where the

parts are produced. This area is composed by twenty-nine injection moulding machines, 8 for

MTS production strategy and 21 for MTO production strategy.

• Quality – It is an area close to the injection process where the non-destructive quality tests were

performed and is different for each production, i.e., each production has its own quality area.

• Quality Laboratory – It is an area located in one of the sides of the production zone and it is

where the destructive quality tests are performed.

Delivery – The final product is loaded in the customer service.

Material Supply - The material arrives the company as raw material.

Injection Moulding - The components are produce through an injection moulding process.

Quality control - Once per hour one moulding is visually analysed by the quality control

technicians and every four hours a moulding is subjected to a destructive test.

Packaging - The produced parts and the ones subjected to a visual control are packed in

boxes and storage in pallets.

Storage - The pallets are storage in a Final product warehouse until delivered to the

customer.

1

2

3

4

5

6

18

• Packaging – It is an area close to the injection process where the products are packaged. Each

production has its own packaging area close to the respective injection machine.

• Folder Warehouse – It is an area located on the side of the production zone where the

mould/product’s information folders are stored.

• Mould Warehouse – It is an area located in the opposite side of the Folder’s warehouse, and is

where the moulds are storage when the product is not in production. It is also the place where

the mould maintenance team works.

• Discharges zone – It is an outside area where the contaminated material and the discharges

were storage until being sold.

• Warehouse ɪɪ - It is located on the floor above the Injection Moulding and it is subdivided into

three areas:

Final analysis Area – It is the place where samples of products are analysed to guarantee the product’s

quality.

• Final Product warehouse– It is the area where the pallets of packaged products are palletized

and stored until being delivered to the customer.

• Hopper Dryers Area- It is where the hopper dryers are located.

The equipment required for the production system is divided in equipment for manufacturing and

equipment for storage. The allocation of these equipment’ are dependent on the production strategy as

presented in Table 3-1. All the equipment used in this production system are explained in Annex A.

Table 3-1 Equipment allocation based on the production strategy

Equipment MTS MTO

Injection machine

and Mould Dedicated to the production

Chiller Dedicated to the production Shared by all MTO productions

Hopper dryer Dedicated to the production Shared by the MTO productions that

requires the same material at the same time

Vacuum pump Dedicated to the production Shared by all MTO productions

Forklift

Shared by all productions Palletizer

Shredder machine

A similar procedure is followed for the dedicated or not dedicated employees and its tasks. Thus, the

employees and its tasks per MTS strategy and MTO strategy are the following:

The dedicated employees, due to the continuous production characteristic of the Make-To-Stock existing

production, are organized by teams and per shifts. Each shift has an eight hours’ duration and each

team is composed by:

19

• Project manager – Is responsible for all the manufacturing system, thus it is allocated to all the

production system. A project manager it is only responsible for one production and does not

work by shifts. It is also the person that communicates with the administrative department.

• Team Leader – Is responsible for change the raw materials BigBag coordinate the team, solve

the production problems, perform the Injection machine and vacuum pump maintenance and to

pass the information to the next team leader at the end of the shift.

• Dedicated employees – Are responsible for check the raw material supply, weight and pack

the products, check the cycle time and perform the quality tests.

In the Make-To-Order production strategy, there are no dedicated employees. The production also

occurs 24h per day; thus, the employees work by shifts. Each shift has an eight hours duration and each

team is organized as follows:

• Project manager – Is responsible for the same topics as the project manager for MTS

productions, with a difference that in this case it is responsible for all the MTO productions.

• Team Leader – Is responsible for start the productions and consequently the machines,

coordinate the team, solve the production problems and to pass the information to the next team

leader at the end of the shift.

• Leader supporter – His task is to perform the Setup activity, support the Team Leader by

helping him to solve the problems, check the raw material supply and perform the maintenance

activities to each injection machine.

• Semi-Dedicated employees – They are responsible for weight and pack the products, check

the cycle time and perform the quality test, visual and destructive. The employees are semi-

dedicated because they can work in more than one Injection Machine (manufacturing process).

All the information presented above supports the MFCA analysis in terms of data collecting and

company’s organization for posterior flow characterization.

3.1.2. The injection moulding machine and process

As exposed in the second chapter the MFCA is a method that needs a detailed knowledge concerning

all production system variables. Thus, to identify and allocate accurately all the materials and energy

flows it is important to understand the injection moulding phases.

The injection moulding process is the most adaptable process for the manufacture of plastic

components. This process is mainly used in mass production and allows the manufacture of products

with several shapes, dimensions and sizes. Nowadays is considered as the preferable process to

produce three-dimensional products with complex shapes [20].

In 1946 James Watson Hendry, idealised and made the first screw injection machine. The rotational

property of the screw allows a better injection speed control as well as the quality of the manufactured

20

products. This type of machine provided the opportunity of mixing materials (recycled with virgin or multi-

coloured). The screw allowed the reduction of the energy consumption, supporting the plastic heating

process through the friction of the bands. Nowadays the screw injection machine represents

approximately 95% of the injection moulding machinery [20], [21].

There are three types of injection moulding machines: electric, hydraulic and hybrid. Since the products

studied are produced by electric and hybrid moulding machines only these two are explained.

The electric injection moulding machines have been increasing its popularity in the last years. This type

of equipment uses several servo-motors for injection, plasticizing, clamping, ejection and each

sequence is controlled by an independent servo-motor, allowing an energy consumption lower than

hydraulic machines. These machines do not use hydraulic oil; consequently, it consumes less cooling

water to control the oil temperature. Furthermore, the contamination by oils is also reduced, as well as

the noise level [22].

The hybrid injection moulding machine differs from the electric in the point that it has an hydraulic

clamping unit and an electric injection unit, or the opposite. This configuration allows a higher clamp

force when compared with all-electric machine and a lower energy consumption when compared with

the hydraulic machines [21]–[23].

The Figure 3-2, presents a scheme of an injection moulding machine. This machine is composed by two

main parts, the injection unit and the clamping unit.

Figure 3-2 Scheme of a screw injection machine [24]

The injection unit consists in a hopper that feeds plastic granules to the machine, a screw which is

mounted longitudinally in the barrel, a barrel heated by external heaters and a nozzle that connects both

units. The injection unit is responsible for plasticizing, and for the injection [21] [23].

The clamping unit consists in a clamping mechanism, which can be mechanical, hydraulic, both types

or all- electric. This unit is responsible for closing the mould, as well as for maintaining the pressure

inside the cavity during the injection packaging and cooling processes. It is also responsible for opening

the mould and extract the injected component. The clamping force depends on the product projected

area [21], [23].

21

The injection moulding process or usually named as moulding cycle (Figure 3-1) starts with the feeding

of the raw material in the hopper, before its entrance in the screw. At this point, the screw transports the

material into the screw channels, which are located inside of the barrel which in turn is heated by external

heaters. During this process, the material is subjected to the rotational movement of the screw,

contributing to the material mixing. Due to the fact that the material is subjected to high temperatures

and is forced to pass in small areas he is compressed and melted. As soon as the material achieves the

screw tip, the melt retracts against a back-pressure surface allowing the accumulation of a “shot”. The

“shot” is the volume of material that the injection unit needs to inject to guarantee the complete filling of

the cavity. Once the appropriate volume of the shot is obtained the screw finishes its rotational

movement and the injection phase starts [20].

On the injection phase, the screw starts his longitudinal movement, with programmed values of speed

and pressure. When the screw is moved forward, the melt is injected inside the cavity until the cavity is

filled leading to the packing phase. On the packing phase, the screw maintains the forward position

while the material solidifies and contracts. Then a small amount of melt is injected to compensate the

material’s contraction. This step finished the packing phase and initiates the cooling phase. During the

cooling phase the pressure and the temperature decrease gradually inside of the cavity. When the

temperature of the material achieves the ejection temperature, the mould opens, and the product is

ejected. After the mould close and a new injection cycle begins [20].

Figure 3-3- Scheme of the injection moulding process adapted from Biswajit, S et al.(2015),[25] and injection moulding cycle [26][27]

A complete cycle of the mould is designated as moulding cycle time and is one of the most important

parameters in the injection moulding process. The cycle time determines the time to manufacture a part

or group of parts, and it also influences the quality of the parts [28].

The injection process also requires other devices, apart from the mentioned injection machine, as the

mould and its cooling system, and the temperature controllers. The mould is one of the most important

tools. It is constituted by the cavity and the core and is made of stainless or aluminium. Depending on

the product and the machine capacity the mould can have one or multiple cavities which can be equal

or different from each other. The mould also needs a feeding system (runner) which can be of two types:

Moulding Cycle

Plasticization Injection Packing Cooling Ejection

22

hot runners and cold runners. The hot runners’ type is a feeding system divided in two parts, the

manifold, which is responsible for carry the melted material to a point close to the cavity, and the drops,

which carries the material from the manifold to the cavity to feed it. In this feeding system, the runner is

not ejected with the part. In opposition, in the cold runner system, the material of the runners is cooled

and then extracted along with the parts [29][30].

The main difference between the feeding systems presented, are the following. On the one hand, the

hot runners’ system allows a lower cycle time, derived from the fact that only the parts need to be cooled.

Consequently, this type of system presents a lower cooling time; however, its maintenance and mould’s

production are more expensive than the systems that use cold runners. On the other hand, in the cold

runners’ system, the runner is ejected with the part contributing for waste of material [31].

3.2. Dissertation Approach

The approach followed to achieve the goals of the present dissertation is described in this section. It is

subdivided into three phases and schematically presented in Figure 3-4.

The first phase consists in the application of the MFCA to an injection moulding unit which follows an

MTS strategy. This unit uses five all-electric machines and one hybrid, and the moulds have a feeding

system with hot runners. As explained before, the MFCA application requires a detailed characterisation

of the production system aiming to analyse and quantify the material flow involved in physical units, and

lately, in monetary units. This information had to be gathered and posteriorly inputted in the calculation

model developed for the analysis and its results analysed. Due to the necessity of an extensive data

collection, a three moths’ internship was required. The results were presented and discussed with the

company’s managers.

The second phase of this work is based on the careful observation of the same production system. This

detailed observation evinces the existence of some production problems that the MFCA is not able to

transmit clearly in its calculation output due to its nature. Thus, a study of similarities between the MFCA

and the Lean tools was performed to access the viability of their integration. Subsequently, a

methodology to integrate MFCA and Lean tools was developed, proposed and further validated. This

methodology aims to complement both method/tool taking advantage of each other. In one hand, the

MFCA mapping costs and require detailed data gathering, on the other hand, the Lean tools adds

significance information from the production system point of view and ha specific tools for root-cause

and problem-solving analysis.

The combination of these powerful tools will allow the company, not only, the mapping of all production

system’s waste related, but also, it is able to highlight production issues and, using tools for root-cause

analysis to identify the root causes of the problems and propose solutions. After all, the methodology

23

will allow the assessment of the improved results in terms of monetary values and physical

consumptions.

Finally, the methodology is supposed to be used to improve the production process by presenting the

impact and the improvement opportunities in monetary values to motivate managers for a continuous

improving system.

Concluding, the present work aims to validate the previous points described by the application of the

MFCA to a continuous production system to evaluate the benefits of its application as a diagnostic tool

of the production system (Chapter 4). Then, during the data collection for MFCA analysis the production

procedure is also carefully observed and studied to understand the production issues that the MFCA

cannot directly identify. Then, a literature review concerned the identification of complementarities

aspects between the MFCA and Lean is performed. Afterwards, a methodology to integrate the MFCA

and Lean tools is proposed and primarily validated with a second case-study based on MTO strategy.

(Chapter 5).

MFCA application to a production system who follows a MTS strategy.

Based on the careful production system observation some MFCA lacks

scope are identified and primely complemented with Lean tools

To support the observation performed a literature review concerning MFCA

and Lean tools is performed

A methodology to integrate MFCA and Lean tools is proposed and then primarily validated

through its application to an injection production system who follows a MTO strategy

Figure 3-4 Approach followed to develop the present work.

24

4. MFCA application in a production system which

follows an MTS strategy

The company’s production system was generally described in the previous chapter. The two types of

productions were introduced and described, as well as the process used to manufacture the studied

part.

This Chapter presents the methodology followed for the MFCA application, based on ISO standard

14051 [3] . It also explains the required process for the data collection, the calculation model developed

to analyse this production system and the obtained results. Moreover, derived from a careful observation

performed in addition of MFCA some improvement suggestions are presented at the end of this chapter.

4.1. Case-Study’s Preparation

The MFCA methodology for application suggests that firstly, the production system must be

characterised. The characterisation process includes a clear definition of the company’s areas and the

determination of the system boundaries and scope [3]:

1. Specify the boundaries and the product to be analysed;

2. Definition of the time period of analysis and data collection;

3. Determination of the quantity centres.

The product studied is entirely produced by the company, thus the boundary was defined as the limits

of the manufacturing system; i.e. from the material supply until the product delivery to the customer.

Therefore, the boundary conditions are defined at the limits of the production process of the Product,

including human resources and departments involved on the process.

The product, designed in this dissertation as Product A, was selected based on its economic significance

for the company. This product is divided in two components, which are produced separately although

their production is synchronised to guarantee an equal production volume to manufacture the entire pair,

avoiding unwanted stocks. The final product is assembled by an independent company. Both parts are

produced through the injection moulding process, using the same raw material. Although, the raw

material feeding system is the same for the production of both parts each production has allocated

particular machines and moulds as well as employees. The characteristics of the Product A are

presented in the following Table.

Table 4-1 Characteristics of the product A

Parts of the Product A Material Weigh [g]

Part 1- Lid

Polypropylene 2.3

25

Part 2- Cup

Polypropylene 4.2

The time period of analysis was defined as one month to allow the collection of reliable data enabling

the identification of the production’s fluctuations as well as the comparison with the logistic records which

in turns are monthly organized. Once the boundary conditions and the period of analysis are defined,

the following step of the characterisation is the determination of the quantity centres, which is presented

in the next subsection.

4.1.1. Quantity Centres determination

The Quantity Centre (designated as QC) determination is performed based on the process information.

Consequently, is mandatory to analyse and identify all the processes (non-adding value and adding

value) involved in the production system, within the case-study's boundaries.

The MFCA intends to divide the production system into processes or parts, the QC, in which the material

is transformed, stored or contributing for the Work-In-Process. However, if a process does not represent

a significant contribution, it can be included in another QC. To support the QC definition, the production

flow was analysed following the material flow within the manufacturing process.

The manufacture of the product starts in the raw material area when the BigBag is positioned in the

supply zone. Then the raw material flows from the BigBags to the hopper dryer through a conduction

system by the action of a vacuum pump. Then, the material is distributed to the injection machine where

the parts are produced. The parts fall in a conveyor belt and then into carton boxes, which are tagged

and stored in a pallet before going to the warehouse. When the pallet is completed, the employee sends

it to the Final product area where it is palletized. After that, the Final product area’s employee stores the

pallet until it is delivered to the customer.

Figure 4-1 illustrates the material flow map developed based on the production system previously

described. In this flow map the determined QC are showed, as well as the flow of material, in terms of

the input and outputs flows of both parts. The flows are divided in positive and negative product’s flow.

26

Figure 4-1 Production of product A – Material flow map

4.2. Quantification of the material flows

Once defined the quantity, centres ISO 14051 [3] suggests that the inputs and outputs of each QC

should be identified. As explained in the literature review, the usual inputs are divided in material and

energy; and the outputs in product and material loss. For the present case study, the energy and energy

losses are included under the product and the material wasted respectively. For this reason, the energy

flow is included in the material flow and they are traced in the MFCA output as a single one for this

specific case-study.

To quantify the material, flow a two steps procedure was used:

1. Determination and classification of all the materials involved;

2. Data compilation to quantify the flows in physical units.

4.2.1. Materials determination and classification

MFCA classifies the material in two categories, the materials and the operating materials[3]:

MFCA boundary

Product

Waste

Waste

Input

Raw Material

Area

Injection

Machine

Part 1-Lid

Quality

Control

Waste management

(Defective)

Hopper dryer

Packaging

Waste management

(Contaminated)

Injection

Machine

Part 2-Cup Quality

Control

Packaging

Waste management

(Contaminated)

Final Product

Warehouse

Waste management

(Defective)

Input Material flow

Positive product flow

Negative product flow

QC-Production of Part 1 and Part 2

QC-Production of Part 1

QC-Production of Part 2

27

• “Materials” are all the materials which become a part of the final product;

• “Operating Materials” are the materials which do not intend to be part of the product.

The present production system inputs only one material, polypropylene, which is used to produce the

whole product. This material follows the entire production system, and no other raw material is added to

it. However, in the packaging and final product warehouse phases, there are auxiliary materials used to

pack the product (Table 4-2). The cost of the auxiliary materials is allocated to the input flow of the QC

and is part of the QC product output. However, if the amount of auxiliary material wasted was significant,

that amount should be allocated to the material waste flow directly.

Table 4-2 Product A- Auxiliary materials identification

QC Product Auxiliary materials and flow identification

Packaging Part 1

Part 2

Carton boxes and plastic bags with different sizes for

each product, tags with different colours for each

product, adhesive tape, pallets and foam paper. This

auxiliary materials’ costs are added to the respective QC

input flow.

Final Product Warehouse Part 1

Part 2

Plastic film used to palletize the final product pallets. It

cost is added to the QC input flow.

During the production system, the polypropylene is wasted for different reasons:

1. Contaminated parts – Parts which fall out of the conveyor belt;

2. Part 1 Quality control test- Due to the destructive character of the quality control test;

3. Discharges of materials performed after a programmed or non-programmed stop;

4. Products which are out of specification- usually the first twenty shots after a stop of the

machine;

5. Defective parts which are returned from the client.

Subsequently the material’s waste data is inputted in the waste management quantity centre for

contaminated or defective products depending on its the losses nature.

The equipment’s maintenance requires the use of operating materials as alcohol, cleaning solvents,

cleaning cloth, mass etc (Annex C). The cost of these products is assigned to the input flow of the QC

where there are used and is always part of the QC waste output due to its nature.

4.2.2. Procedure Followed to Collect Data in Physical Units

The next phase is the quantification in physical units of each input and output. The ISO norm suggests

that for the material quantification only one physical unit should be selected [3]. Thus, the raw material

is quantified in mass units. However, due to the difficulties founded in measuring the operating and

auxiliary materials in mass unit, these elements are quantified in units of product used, i.e. number of

28

cleaning cloths used in each maintenance, the number of adhesive tape tubes used during the selected

period etc.

The procedure selected to quantify the flows involved has a direct influence on the calculation model

and on the MFCA results. Thus, the data gathering procedure and quantification should be selected

carefully and should be programmed to cause the least possible disturbance to the operators and to the

process. Moreover, this phase is the longest and laborious one, once it involves the communication with

several departments to adapt the data collection time with the working labours time and to adapt the

auxiliary calculation models with the company’s records availability.

In some QC the physical collecting data was not possible or easy to accomplish, as the total production

volume quantification in terms of material consumed and parts produced. To overcome this issue an

auxiliary calculation model was developed for the specific case. The development of the auxiliary

calculation model is further explained.

The procedure followed for the quantification of the input and output flows is divided into two categories:

the Shop floor measurements and the company’s records analysis. The tasks performed are listed and

explained in Figure 4-2.

The first step of the procedure is the BigBag's daily counting in the Raw Material division. Thus, every

day at the same time the number of stored BigBags were accounted to estimate the raw material

consumption value to produce both parts. Based on the fact that during the collection period any

anomaly was detected between the raw material division and the hopper dryer, it is assumed that there

is no waste of material between these points. This assumption is also valid for the material that flows

from the Hopper dryer to the injection machines.

The next steps of the procedure are the machine’s waste weighing, namely the defective parts, the

dischargers and the contaminated components. Thus, depending on the waste nature it was measured

daily or weekly. The defective parts measurement was performed every day at the same time. This

procedure was first performed to assess the accuracy and reliability of company records. At the end of

the first week of measurements, it was possible to conclude that the registers do not transmit the real

Shop floor Measurements Records Analysis

BigBags’ daily counting;

Defective parts daily weighing;

Dischargers of raw material weighing;

Contaminated parts weekly counting;

Operational cavities per mould daily

counting.

Daily production results registered by the

employee (including parts produced, cycle

time each four hours and machine stops);

Internal production management software

data compilation (including cycle time and

machine stops)

Update the developed Calculation Model

Figure 4-2 – Data collecting procedure

29

waste value. Therefore, for the rest of the data collection period it was necessary to weigh the rejected

parts every day. For that purpose, it was asked to the team leader to separate the defective parts of the

two parts of the Product A. The discharges were measured when the maintenance occurred, and the

contaminated components were daily weighted.

The parts destroyed in the quality control test performed to Part 1 were weighted together with the

defective parts. Thus, the amount of waste derived from the quality control test was calculated based

on the developed auxiliary calculation model. The quality control test performed to Part 2 is non-

destructive. After it, they are stored for six months as a batch quality sample and then are delivered to

the customer.

The next step of the procedure is related to the number of operational cavities of each machine. This

value is collected to be further introduced in the auxiliary calculation model to appraise the real

production volume when combined with the cycle time and the machine stops.

The last step is the analysis of the available data existent in a company’s internal software. This software

receives from the machine all the machine’s stop, the real cycle time and the number of components

produced and rejected. Due to incongruences found in the data, only the values related to the stops and

the cycle time were extracted. Once all the data was collected, it is introduced in the Auxiliary Calculation

Model to calculate the real production volume and the total material consumed during the production

process. Figure 4-3 describes the approach of the calculation model.

The Auxiliary Calculation Model calculates the production volume and the material consumed per part

and per machine. The daily production volume of each machine is calculated using Equation (4.1) where

𝑛𝑝𝑎𝑟𝑡𝑠 is the number of parts produced per day, 𝑡𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 is the production time in hours per day, 𝑡𝑐𝑦𝑐𝑙𝑒

is the time required to produce one moulding, and 𝑁𝑐𝑎𝑣𝑖𝑡𝑖𝑒𝑠 is the number of operational cavities of the

mould. The 𝑡𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 is calculated using Equation (4.2) where, 𝑠𝑡𝑜𝑝𝑠 is the time that the machine is not

producing any component. The total amount of good parts produced, 𝑛𝑔𝑜𝑜𝑑 𝑝𝑎𝑟𝑡𝑠, is calculated by

Equation (4.3) where 𝑛𝑑𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒 represents the rejected parts, 𝑛𝑞𝑢𝑎𝑙𝑖𝑡𝑦 is the number of parts destroyed

in the quality test, and 𝑛𝑐𝑜𝑛𝑡𝑎𝑚𝑖𝑛𝑎𝑡𝑒𝑑 is the number of contaminated parts. The total amount of consumed

material is calculated using Equation (4.4) where 𝑤𝑒𝑖𝑔ℎ𝑡𝑝𝑎𝑟𝑡 is the weight of each part, and

𝑤𝑒𝑖𝑔ℎ𝑡discharges is the amount of discharged material.

Cycle time

Number of cavities

Rejected parts and Material Weigh

Machine’s stops

Production volume

Material consumed

Figure 4-3 – Auxiliar calculation model approach

30

𝑛𝑝𝑎𝑟𝑡𝑠 = 𝑡𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛[ℎ] × 𝑡𝑐𝑦𝑐𝑙𝑒[ℎ] × 𝑁𝑐𝑎𝑣𝑖𝑡𝑖𝑒𝑠 (4.1)

𝑡𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 = 24[ℎ] − 𝑠𝑡𝑜𝑝𝑠[ℎ] (4.2)

𝑛𝑔𝑜𝑜𝑑 𝑝𝑎𝑟𝑡𝑠 = 𝑛𝑝𝑎𝑟𝑡𝑠 − 𝑛𝑑𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒 − 𝑛𝑞𝑢𝑎𝑙𝑖𝑡𝑦 − 𝑛𝑐𝑜𝑛𝑡𝑎𝑚𝑖𝑛𝑎𝑡𝑒𝑑 (4.3)

𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑐𝑜𝑛𝑠𝑢𝑚𝑒𝑑[𝐾𝑔] = 𝑛𝑝𝑎𝑟𝑡𝑠 × 𝑤𝑒𝑖𝑔ℎ𝑡𝑝𝑎𝑟𝑡[𝐾𝑔] + 𝑤𝑒𝑖𝑔ℎ𝑡discharges[𝐾𝑔] (4.4)

The 𝑡𝑐𝑦𝑐𝑙𝑒 and the 𝑁𝑐𝑎𝑣𝑖𝑡𝑖𝑒𝑠 are introduced every four hours to provide a result as close as possible to

the reality. The number of good parts produced allowed the calculation of auxiliary materials used per

week, per Part of the product.

The presented calculations were performed every day during the collecting period. After one month, the

global results were compared with the logistic records. The logistic records include the information of

the stock records, number of pallets of each product delivered to the customer as well as the number of

pallets of each part stored in the Final Product Warehouse. The stock records include the raw material

and the auxiliary materials stocks. Consequently, the raw material consumption observed and accounted

was compared with the stock records and number of pallets delivered to the customer during the

established period. In turn, the same records allow the validation of the auxiliary materials used based

on the total amount of pallets delivered and stored during the analysis. Furthermore, the logistic and

warehouse records also supported the calculation of the operating materials consumed. Moreover, the

consistency of the obtained results allowed the validation of the auxiliary calculation model itself and the

quantification of the material flows in physical units, for each QC.

Regarding the operating materials, there are four types of maintenance: shiftily, weekly, monthly and

annually with different characteristics. Therefore, as a first approach, at least two shiftily maintenance

performed by each team leader were accounted and the materials consumed estimated. Then, some

interviews were performed to appraise the materials’ usage discrepancy between each operator, and

finally a meeting with the maintenance responsible to understand the process needs. At the end, this

information was combined with the operating materials records and the material consumed estimated.

The last step of the material flow quantification in physical units is the mass balance within each QC

and in the total production. The material input of each quantity centre and its inventory must be equal to

the output, in terms of product and waste. Once all the material quantities are determined and the

balance is confirmed, the next phase is the material flow quantification in monetary units.

31

4.3. Quantification Energy, System and Material Flows

in monetary units

The physical units measured in terms of input and output must be translated in monetary units for each

QC. The production system cost includes all the monetary expenses incurred to perform the activity.

Consequently, all cost that are associated or generated by the material flow must be allocated to the

respective output flow (product or material waste). According to ISO standard 14051 presented in [3]

the accuracy of the analysis is maximised when all costs are calculated from data available for individual

QC and material flows. However, when this is not possible the cost should be estimated by cost

allocation procedures.

There are four types of costs considered by the MFCA, the Energy Cost, the System Cost, the Material

Cost and the Waste management cost. This section presents the allocation procedure used for Energy,

System and Material cost calculation. The Waste Management cost identified in this production system

are exclusively related to the waste treatment cost within the WM-QC, so it cost is directly allocated to

the WM-QC system and no other allocation criteria is required [3].

Energy Cost

The energy cost was calculated individually for each QC. To calculate this cost firstly the equipment

used in each QC were identified, and its power consumption measured using a specific equipment,

PROVA 6830 power and harmonic analyser. Then, the energy consumed during the production process

was calculated using Equation (4.5), where 𝑃𝑜𝑤𝑒𝑟 𝑐𝑜𝑛𝑠𝑢𝑚𝑒𝑑 is the power consumption measured with

PROVA 6830 in Kilowatt, and 𝑡𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 is the total time that the machine worked. Afterwards, the Energy

cost is calculated using Equation (4.6), where 𝐸𝑛𝑒𝑟𝑔𝑦 𝑐𝑜𝑠𝑡 corresponds to the price per kilowatt-hour.

The energy cost is allocated to the correspondent QC.

𝐸𝑛𝑒𝑟𝑔𝑦 [𝑘𝑊ℎ] = 𝑃𝑜𝑤𝑒𝑟 𝑐𝑜𝑛𝑠𝑢𝑚𝑒𝑑 [𝑘𝑊] × 𝑡𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 [ℎ] (4.5)

𝐸𝑛𝑒𝑟𝑔𝑦 𝑐𝑜𝑠𝑡_𝑄𝐶 [€] = 𝐸𝑛𝑒𝑟𝑔𝑦 [𝑘𝑊ℎ] ×𝐸𝑛𝑒𝑟𝑔𝑦 𝑐𝑜𝑠𝑡[€]

𝑘𝑊ℎ(4.6)

System Cost

The System Cost includes all the expenses related to the production flows excepts material and energy

cost.[3] Thus, the System Cost is calculated using Equation (4.7), where the employee cost represents

the total cost of the involved employees per QC; the Space and the Equipment costs are the rent of the

space and of equipment required for QC.

𝑆𝑦𝑠𝑡𝑒𝑚 𝐶𝑜𝑠𝑡𝑄𝐶 [€] = ∑ 𝐸𝑚𝑝𝑙𝑜𝑦𝑒𝑒 𝑐𝑜𝑠𝑡𝑄𝐶[€] + 𝑆𝑝𝑎𝑐𝑒 𝑐𝑜𝑠𝑡𝑄𝐶[€] + 𝐸𝑞𝑢𝑖𝑝𝑚𝑒𝑛𝑡 𝑐𝑜𝑠𝑡𝑄𝐶 [€] (4.7)

Employee’s Cost

32

The employee’s cost includes the cost of each employee involved in the production system.

Furthermore, they must be allocated to each QC based on the tasks performed. The employees’ cost

allocation is based on the time spent performing a determined task or activity.

Nevertheless, this criterion cannot be applied to the Project Leader, since he is responsible for the entire

production line. Thus, together with the Project leader a valid distribution of his works per QC was

defined. The distribution per QC is described in Annex D and is based on the time spend by the Project

Leader in each QC. The project leader cost is calculated using Equation (4.8), where the 𝐶𝑜𝑠𝑡𝑝𝑟𝑜𝑗𝑒𝑐𝑡 𝑙𝑒𝑎𝑑𝑒𝑟

is his salary and 𝑡𝑎𝑙𝑙𝑜𝑐𝑎𝑡𝑒𝑑𝑄𝐶 is the time distribution per QC.

On the other hand, the costs of the team leader and the dedicated employees are allocated to the QC

using Equation (4.9), where 𝐶𝑜𝑠𝑡𝑒𝑚𝑝𝑙𝑜𝑦𝑒𝑒 is the employee’ cost per hour, the 𝑡𝑒𝑚𝑝𝑙𝑜𝑦𝑒𝑒𝑄𝐶_𝑎 is the time in

hours spent by the employee executing the activity 𝑎 related to the QC, and the 𝑁𝑒𝑚𝑝𝑙𝑜𝑦𝑒𝑒𝑄𝐶_𝑎 is the

number of employees involved in this activity.

𝑃𝑟𝑜𝑗𝑒𝑐𝑡 𝐿𝑒𝑎𝑑𝑒𝑟 𝑐𝑜𝑠𝑡 𝑄𝐶 = 𝐶𝑜𝑠𝑡𝑝𝑟𝑜𝑗𝑒𝑐𝑡 𝑙𝑒𝑎𝑑𝑒𝑟[€/𝑚𝑜𝑛𝑡ℎ] × 𝑡𝑎𝑙𝑙𝑜𝑐𝑎𝑡𝑒𝑑𝑄𝐶[𝑚𝑜𝑛𝑡ℎ] (4.8)

𝐸𝑚𝑝𝑙𝑜𝑦𝑒𝑒 𝑐𝑜𝑠𝑡𝑄𝐶[€] = ∑ 𝐶𝑜𝑠𝑡𝑒𝑚𝑝𝑙𝑜𝑦𝑒𝑒 [€

ℎ] × 𝑡𝑒𝑚𝑝𝑙𝑜𝑦𝑒𝑒𝑄𝐶𝑎

[ℎ] × 𝑁𝑒𝑚𝑝𝑙𝑜𝑦𝑒𝑒𝑄𝐶𝑎

𝑎=1

(4.9)

To obtain reliable data for the calculation model the following steps were performed:

1. Identification of the activities per QC;

2. Identification of the type of employee per activity;

3. Analysis of the perception of the employee about the time spent in each activity;

4. Calculation of the time required to perform each activity and the number of employees involved;

5. Data collection of the salary of each type of employee;

The results obtained through are presented in Annex D.

Space’s and Equipment’s Cost

The Space cost is calculated using Equation (4.10). Then, it is assigned to each QC individually based

on the space required to perform the activities involved as well as the space occupied by the equipment.

Regarding that, the 𝑆𝑝𝑎𝑐𝑒−𝑄𝐶 is the space occupied by the QC in square meters, the 𝑇𝑜𝑡𝑎𝑙 𝑆𝑝𝑎𝑐𝑒 is the

total area rented in square meters and the 𝑅𝑒𝑛𝑡 𝐶𝑜𝑠𝑡 is the value paid for the total area per month.

𝑆𝑝𝑎𝑐𝑒 𝑐𝑜𝑠𝑡−𝑄𝐶[€] =𝑆𝑝𝑎𝑐𝑒−𝑄𝐶 [𝑚2]

𝑇𝑜𝑡𝑎𝑙 𝑆𝑝𝑎𝑐𝑒 [𝑚2]× 𝑅𝑒𝑛𝑡 𝐶𝑜𝑠𝑡[€/𝑚𝑜𝑛𝑡ℎ] (4.10)

The cost calculation and the allocation to the QC were performed based on the following approach:

1. Identify the physical boundaries of each QC;

2. Measure the space occupied per each QC;

3. Rent cost and the total area rented data gathering (source-management department).

33

The Equipment’s cost is allocated considering the type of equipment. There are two different types of

equipment, the dedicated equipment and non-dedicated equipment. The dedicated equipment are those

that are only used to produce the component, as the Injection machine, the weight scale, the conveyor

belt… in that case, the cost of the equipment is its rent or monthly depreciation and is allocated to the

QC where is used. To allocate the non-dedicated equipment to the manufacturing system a different

criterion is used. It is known that the majority of this equipment is stopped during a period of the

production system. However, even though they are stopped, they have an associated cost.

Consequently, the company uses this equipment to support others production systems, and their cost

cannot be allocated to a single production system or even distributed by operational time. Therefore, is

assumed that the occupation of non-dedicated equipment by a production process is proportional to its

production volume. Based on the presented statements an rule based on the total production volume is

selected. Equation (4.11) represents the direct ratio between the 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑣𝑜𝑙𝑢𝑚𝑒𝑐𝑜𝑚𝑝𝑜𝑛𝑒𝑛𝑡 which is the

total production volume of the product, and 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑣𝑜𝑙𝑢𝑚𝑒𝑐𝑜𝑚𝑝𝑎𝑛𝑦 represents the company’s total

production volume. Thereafter the Equipment cost is calculated using Equation (4.12), where

𝐸𝑞𝑢𝑖𝑝𝑚𝑒𝑛𝑡 𝑐𝑜𝑠𝑡−𝑄𝐶 is the equipment’s rent or monthly depreciation and is allocated to the respective

QC.

𝐴𝑙𝑙𝑜𝑐𝑎𝑡𝑖𝑜𝑛𝑛𝑜𝑛−𝑑𝑒𝑑𝑖𝑐𝑎𝑡𝑒𝑑 𝑒𝑞𝑢𝑖𝑝𝑚𝑒𝑛𝑡 =𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑣𝑜𝑙𝑢𝑚𝑒𝑐𝑜𝑚𝑝𝑜𝑛𝑒𝑛𝑡

𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑣𝑜𝑙𝑢𝑚𝑒𝑐𝑜𝑚𝑝𝑎𝑛𝑦 (4.11)

𝐸𝑞𝑢𝑖𝑝𝑚𝑒𝑛𝑡 𝑐𝑜𝑠𝑡−𝑄𝐶 = 𝐸𝑞𝑢𝑖𝑝𝑚𝑒𝑛𝑡 𝑐𝑜𝑠𝑡 [€/𝑚𝑜𝑛𝑡ℎ] × 𝐴𝑙𝑙𝑜𝑐𝑎𝑡𝑖𝑜𝑛𝑛𝑜𝑛−𝑑𝑒𝑑𝑖𝑐𝑎𝑡𝑒𝑑 𝑒𝑞𝑢𝑖𝑝𝑚𝑒𝑛𝑡 (4.12)

All the allocation rules results are presented in Annex D.

Material Cost

The Equation (4.13) presents the calculation procedure followed for the material quantification in

monetary units. Where 𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙[𝐾𝑔] is the total amount of material required to accomplish the specific

task.

𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙 𝐶𝑜𝑠𝑡 = 𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙[𝐾𝑔] × 𝐶𝑜𝑠𝑡/𝐾𝑔 (4.13)

The collecting data procedure was presented in the previous sub-section and the material cost obtained

through a meeting with the logistics department.

Output allocation

The energy and system costs are allocated to the output product or waste trough the proportion of mass

ratio between the products and material waste, i.e., the energy consumed in each quantity centre is

assigned to the output flow by the percentage of the total production that corresponds to product and

material losses. For example, the energy costs allocated to the material loss are associated with the

production of defective parts. The same logic is followed for the Space and Material allocation to Product

and Waste.

34

The Equations presented above were applied to each QC to develop a calculation model presented in

the next subsection.

4.4. MFCA compilation data for the Calculation model

The following step of the MFCA application is the data compilation for the Calculation model to analyse

the present production system. After having quantified all types of flows in physical units and defined

the criterion for converting them into monetary units and also the input and output allocation rule, the

calculation model organises all the information previously calculated and at the end exports a final output

flow map where the flow costs are shown.

This model should include all the resources used and the respective costs to appraise the economic

flow (between QC) and overall to assess the economic performance of the entire production system. It

ought to characterise the economic flow of each QC including the costs related to the previous ones

and the internal costs, i.e., the energy, system and additional materials costs required to perform the

activity.

The present production system, as it was exposed before, is characterised for being based on MTS

strategy. Moreover, it works continuously during the entire year without significant variations during this

period. Therefore, the obtained information for the production system during the collecting period can

be extrapolated, obtaining the annual analysis of the manufacturing system.

The material flow should be developed following the process flow, i.e. the first QC which must be

quantified is the QC where the production system begins, in this case, the Raw Material area. Then the

quantification process should follow the material flow presented in Figure 4-1. The following steps

present the approach used for the development of the calculation model for a single QC:

1. Calculate the input cost of the QC, based on the material flow. For the 1st QC, the input cost

usually corresponds to the cost of the imputed material.

2. Identify the operating and auxiliary materials that are related to the QC and allocate them to the

respective output flow.

3. Calculate the costs of the materials presented in the previous step.

4. Calculate the ratio between the product and waste to assign the resources.

5. Identify and calculate the Material inventory and its variance in the QC.

6. Calculate the energy and system cost through the criterion defined to the QC;

7. Allocate the energy and system cost to the QC output flow based on the ratio calculated in the

4th step;

8. Calculate the output flow of the QC, divided in product and waste.

To accomplish the analysis of the total production system and its flow, the procedure presented should

be performed for each QC.

35

The following table illustrates the implementation of the presented procedure for the Part 2-QC- Injection

Machine including the input costs (from the previous Part 2 QC -Hopper Dryer), the resource allocation

and the final output costs.

Table 4-3 Part2 QC Injection Machine

Total Product Waste

Cost k€ Allocation Cost k€ Allocation Cost k€

Inp

ut

Previous QC 1526 98.5% 1504 1.5% 22

Operating Materials 10 0% 0 100% 10

Material Stock 0 98.5% 0 1.5% 0

System 286 98.5% 282 1.5% 4

Labour 51 - - - -

Space 11 - - - -

Equipment 223 - - - -

Energy 43 98.5% 42 1.5% 1

Total Cost k€ 1865 1828 37

In the Injection Machine, the majority of inputs are allocated to the outputs by the ratio between the

material and material loss except for the operating materials since they are used to perform the

maintenance, and consequently those materials do not become part of the product.

The calculation model is then obtained through the application of the procedure to all processes. This

analysis presents the cost flow of the entire production process and allows the company to appraise the

process where the waste has the highest value.

As explained before the calculation model results is a flow map where the material flow cost is presented

through the combination of each single QC. Thereafter, this flow map is analysed based on the material

waste costs

4.5. MFCA application results and its analysis

The calculation model is the last step of the MFCA analysis. Afterwards the results obtained ought to be

communicated to the company’s managers. Then the company’s managers might use that information

to support decision-making in order to improve the production system’s financial performance [3] In this

section, the results obtained from the MFCA analysis to the production system which follows the MTS

strategy are presented and analysed.

4.5.1. MFCA results

The flow map is the final output of the MFCA analysis (Figure 4-4) : it presents the economic flow based

on the resources consumed in each quantity centre. The flow map’s main goal is to map the real waste

value and the production economic flow. Thus, it is divided in QC and then each QC is sub-divided in

Input cost, Energy and System cost and Outputs which in turns differentiate the product and material

36

waste cost (Figure 4-4). The present flow model also shows the distribution in percentages between

QCs to allow the analysis however it is not mandatory for the MFCA analysis output.

Figure 4-4 Flow maps obtained from the MFCA calculation model

Form the analysis of the Figure 4-4 is possible to analyse the process or processes within the total

production system where the materials waste increases its cost. The MFCA flow map show that the

single QC with the highest waste cost is the QC – Injection machine of Part 2 wasting 37k€ per year,

38%

62%

99.8%

0.2%

8.8%

91.2%

8.1%

91.9 %

2.1%

97.9%

37

followed by the Quality Control QC of Part 1 which wastes 36k€ per year and then the QC – Injection

machine of Part 1 that generates a waste cost of 34k€.

Moreover, is possible to analyse the Part of the product which represents the highest cost contribution

for the total waste cost. These calculations are performed considering only the waste cost of the Waste

management QCs (contaminated and defective). Following the waste flow (red arrows-Figure 4-4)

individually of each part, the production system of the Part 1 wastes 81k€ per year and the production

system of the Part 2 wastes 45k€ per year.

Furthermore, is also possible to analyse the final cost of the production process per Part. The product

cost of the Part1 production process is 1449 k€ per year and for Part2 is 2051k€ per year, these values

are presented in QC-Final product (output-product) of Part1 and Part2 respectively.

The analysis of the production system is performed based on MFCA output (Figure 4-4) which include

the costs flow of the production system divided per QC. Moreover, to analyse the manufacturing system

a complementary analysis is required, the type of analyse or it scope is not specifically included in MFCA

standard or guidelines; only vague directions are provided as a suggestion of the way that those results

should be presented [3].

4.5.1. Complementary analysis based on MFCA results

The posterior analysis of the MFCA results and possible conclusions, which are not included in the

MFCA output Figure 4-4, is dependent of the analyser abilities to detach some critical points within the

production system and to perform the necessary comparative analysis. The present section aims to

present the analysis performed after the MFCA output and is totally performed by the analyser.

From the MFCA direct results is possible to build further analysis, that depend on the study aims and on

the analyst/company needs. For this case study is important to analyse the primary causes of the

material waste and its financial impacts.

From the values presented in Figure 4-4, is possible to calculate the cost distribution per part that

constitutes the product. For the sum of the product cost of each part, considering the material distribution

after the hopper dryer QC is possible to achieve the cost of the Part 1 and Part 2. Moreover, following

the same procedure is possible to calculate the waste cost per part and consequently for the total

production. These calculations are organised in Table 4-4.

Table 4-4 Production cost distribution per part

Product Cost k€ Product Cost Waste Cost k€ Waste Cost

Part 1 1 449 40,0% 81 2,2%

Part 2 2 051 56,6% 45 1,2%

Total 3 499 96,6% 126 3,4%

The complementary analysis performed based on the MFCA results (Figure 4-4) together with the

observation to the production system allows the identification of some critical points and primary

suggestions for their causes.

38

The complementary analysis of the overall results shows that 96.6% of the total cost is related to the

production of parts with the required specification to deliver to the customer and 3.4% is related to

material losses (Table 4-4).The production of Part 2 represents more 15.6% of the total cost than the

manufacture of Part 1, this value can be a consequence of the Part2 characteristic. Thus, a primary

analysis to assess the cause of this difference pointed that the hopper dryer needs to supply more 1.85

grams of raw material than to produce one Part 1.

Moreover, the cost associated with the material waste is 1% higher in the production of Part 1 then in

the production of Part 2 (Table 4-4), the complementary analysis relates this difference with the

destructive test performed in the quality control of Part1. Furthermore, if the parts production were

analysed separately is possible to assess that: 5.3% of the cost required for the Part1 production is

related to material loss this value is due to the destructive test performed during the quality control of

Part1.

The complementary analysis also identifies the cost contribution of each QC divided in Product and

Waste, and the contribution to the total production cost based on the cost increased in each QC (product

or waste) within the total production cost (Table 4-5). These results are obtained through a cost

distribution, where the Product k€ is related only with the cost of energy, system and material stocked

incurred in the QC which becomes product and the same for the Waste k€.

Table 4-5 Added cost per QC and total contribution

Product k€ Waste k€ Total contribution

Bo

th

Raw Material Area 2 460.6 0 67.9%

Hopper Dryer 2 0 0,1%

Par

t 1

Injection Machine 279.2 33.5 8.6%

Quality control 0 36.6 1,0%

Packaging 217.0 0 6.0%

Waste Management (Contaminated) 0 -0,1 -0,003%

Waste Management (Defective) 0 4.0 0,1%

Final Product Warehouse 18.1 7.3 0,7%

Par

t 2

Injection Machine 297.8 36.6 9,2%

Quality control 34.0 0 0.9%

Packaging 170.0 0 4.7%

Waste Management (Contaminated) 0 -0,1 -0,003%

Waste Management (Defective) 0 5.0 0,1%

Final Product Warehouse 21.0 3.6 0,7% Total Cost k€ 3499.5 126.4

The results obtained, Table 4-5, pointed that in the Raw Material is the QC where the product has the

highest cost representing 67.9%, followed by the Part2 Injection Machine, Part1 Injection Machine QC,

and QC-Packaging of Part1 and Part2.

After the analysis presented in Table 4-5, the cost contribution of each QC-section within the incurred

cost of each QC divided in product and waste is presented in Figure 4-5 and Figure 4-6 respectively.

This complementary study is performed to support the knowledge within each QC which QC-section

39

represents the highest contribution cost and based on that support the stakeholder to re-plan their

strategy.

Figure 4-5 Contribution of each parameter for the QC’s product cost

The Raw Material QC cost is pointed as a consequence of all material required for the product

manufacturing is inputted in this QC. All the cost of the material required represents approximately 98%

of the total Raw Material Cost QC-cost which has a high influence in the production system economic

performance.

The followings QCs with the higher contribution cost are the Part 2 and Part1 – Injection Machine, (Table

4-5) which is considered as comprehensible due to the type of production in studying. The difference

between them is related to the amount of material injected into each production system and also the

depreciation cost of the machines which varies depending on the acquisition cost. Also, the energy

required to produce Part 2 is higher than the required to produce Part1 (Figure 4-5). Those two QC are

the ones that contribute more to the total waste cost, which is directly related to the percentage of the

material wasted since the cost allocation is performed based on the material waste (Figure 4-6). The

material wasted in the production of Part1 and Part2 is distributed as 91% and 92% due to defective

Part1, and Part2 produced respectively and 9% and 8% with contaminated and discharges.

The following QCs with the higher contribution cost are the Packaging for both parts (Table 4-5). This

high value is a consequence of the procedure to pack each part which is entirely performed by the

20%

46%

11%

52%

98%

29%

54%

98,6%

15%

48%

47%

15%

14,47%

1,38%

6%

0,05%

0,5%

65%

4%

0,04%

67%

73%

0,16%

45%

0,14%

0,7%

3%

37%

0,11%3%

13%

0,38%

12%

10%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Final Product Warehouse

Waste Manag.(Defec.)

Packing

Quality control

Injection Machine



Packing

Quality control

Injection Machine

Hopper Dryer

Raw Material Division

Pa

rt 2

Pa

rt 1

Bo

th

Pro

du

ct

Material Operating Materials Employee Equipment Space Energy

Contribution of each parameter for the QC’s product cost

40

employee. The complementary analysis allows the recognition of some issues and some improvement

suggestions were described further. Moreover, the packaging phase is where all the auxiliary materials

were inputted which also contributes to the QC cost.

The complementary analysis performed based on the MFCA flow map aims to present and try to point

the reasons behind the waste cost value. Thus, this analysis pointed the QC-Quality control of Part1

and the Injection Machine Part 2 as being the QCs with the highest cost value. Some reasons behind

the waste cost of the QC-Injection Machine Part 2 were already presented, however, is also important

to refer that this cost is also influenced by the operating material needed for the daily machine

maintenance (Figure 4-6).

The material inputted in the Quality control of Part1 is material wasted, and its high cost comes not only

from the material waste cost but also the fact that this process is performed by the employee once per

hour, thus, his cost is allocated to this process. Moreover, once a shift a quality technician performs the

same test increasing the process cost since a specialised employee requires a higher cost per hour.

The Waste Management of defective components also contributes to the waste cost increase. This

process is required from the customer for design confidentiality reasons, and the company is forced to

grind all defective parts and all returned parts from the customer. Thus, this cost comes from the

employee cost who perform this task and from the machine used.

In the next section, some improvement suggestions based on the complementary analysis performed

are presented.

0,2%

0,5%

3%

3%

48%

0,22%

57%

99%

0,3%

25%

0,95%

10%

0,4%

1,3%

26%

0,05%

31%

0,4%0,1%

1,4%

0,18%

2%

0,2%

0,0% 20,0% 40,0% 60,0% 80,0% 100,0%



Packing

Quality control

Injection Machine



Packing

Quality control

Injection Machine

Hopper Dryer

Raw Material Division

Pa

rt 2

Pa

rt 1

Bo

th

Wa

ste

Material Operating Materials Employee Equipment Space Energy

Figure 4-6 Contribution of each parameter for the QC’s waste cost

Contribution of each parameter for the QC’s waste cost

41

4.6. MFCA application conclusions

The MFCA analysis applied to the product’s production system supports the idea that this method can

be used to assist the company to understand the current state of its production system in terms of

monetary units. In addition, it reveals that MFCA allows an overall understanding about production

system’s cost flow by mapping the material’s movements. Concluding, this method can help to map and

support the analysis of the costs flows as well as the impact of the waste cost in the total production

system.

Before the application of MFCA, the company believed that the waste of material per material input of

this production line was lower than 1%. This is a consequence of company’s traditional cost accounting

method that estimates the waste cost calculation through the comparison between the raw material area

and the final product warehouse data However, when the auxiliary and operating material are included

to the MFCA application, the result obtained shows that the real material waste value represents more

than 3% (2.2% due to Part1, 1.2% due to Part2).

Moreover, this method can be applied as a diagnostic tool when combined with a careful observation to

detect wastes of material and resources during the production system. For those cases some

improvements were suggested:

• Reduce the number of mouldings rejected after stops - The defective parts are a consequence

of the defective products which are produced after the daily maintenance performance that

requires in theory twenty modulations until achieving a specified component. This assumption

motivated a detailed analysis to assess the possibility of material waste reduction.

Consequently, the 5th, 10th, 15th and 20th moulding after maintenance were subjected to a quality

control test. From the analysis of the results obtained was possible to conclude that after the

5th moulding each part met the requirements needed to be delivered to the customer. This

improvement would allow a saving more than one million products per year. (Annex E)

• The quality control destructive test performed to Part 1 is one of the major sources of waste

cost and material waste. Since the samples often present results within the required values,

the test frequency could be redefined. However, this quality control frequency is required from

the customer and consequently cannot be redefined, in that case, is suggested to train the

employees in order to eliminate the test performed by the quality technical, decreasing the QC

cost.

The careful observation of production system combined with the analysis of the MFCA application

allowed the recognition of some technical issues which increase the production cost and material waste.

The results of this analysis suggest that:

• The Hopper dryer QC should be eliminated from the production system. It is a total waste of

resources. This QC is not fundamental to the process, since the material used do not need to

be dryer consequently this QC is increasing the Work-In-Process.

42

• The moulds maintenance should be scheduled to obligate the mould maintenance after a

determined number of moulding. This action will avoid the existence of inoperative cavities

resulting in an improvement in material and energy use.

• The Raw Material aspiration system should be modified since it represents 27% of the Leader

work.

• The packaging phase should also be reformulated since the employees spend more than sixty

percent of their work in this activity. A layout change could be enough to decrease that value

avoiding produced part’s queue to be weight.

The actions suggested should be supported by a cost analysis to assess its consequence on the total

production cost.

The MFCA analysis is a significant tool to evaluate and comprehend the real waste cost and its impact

on a production system. It aims to motivate managers and engineers to re-define their strategy based

on the waste cost and the environmental and economic impact. The MFCA method is concerned about

the reduction of production costs through the decreasing of material consumed that can pass by the

material waste reduction. To perform this analysis a detailed and extensive data is required which could

also be used to enhance the company’s information and accounting system, offering a precise data for

future project decisions. Moreover, it could be a useful diagnostic tool to recognise some production

issues during the analysis and collecting data period when combined with a visual analysis.

The MFCA analysis is able to assess all material and resources waste based on an extensive data and

system characterization but is not prepared to recognise and deals with inefficiencies from the

manufacturing system point of view. In fact, after obtaining MFCA results is necessary to perform several

analysis to be able to conclude the overall performance of the system and its limitations. Moreover, the

extensive data collecting required from the MFCA analysis can be used for further systematic analysis

allowing the easy identification of critical points. This conclusion, and the necessity of a detailed

observation of the production system to propose solutions and assess some root causes of the material

waste motivated a study concerned about the possibility of integration MFCA with Lean tools.

43

5. Methodology for MFCA and Lean Tools Integration

The MFCA is a method to diagnose production systems based on the quantification of the material flows

separating de material used to manufacture the product from the material losses (waste). It allows the

identification of inefficiencies throughout the production system and presents the results regarding

product and waste cost flows. During the development of the first case study, presented in the previous

section, the MFCA allowed the identification of the waste in each QC and the sources of that waste.

Nevertheless, no information is provided about the critical level of those wastes (no target or benchmark

is defined) neither the root causes are systematically identified.

The MFCA maps and quantifies the places (QCs) and the amount of resources consumed, as well as

the material (and energy) losses. However, does not include a procedure for supporting the subsequent

phases of the diagnosis and implementation of improvement measures. Which includes: (i) the

identification of the critical QCs, (ii) the identification of the critical production steps or task in each QC,

(iii) the identification of the root causes of unnecessary resources consumption and losses; (iv) and

finally, the definition of the type solution required.

Thus, as it was referred to the previous case study, the use of Lean manufacturing related tools after

MFCA is recommended for the following reasons:

i) To identify the QC which has a critical value of waste (based on user experience and

its sensibility to assess the results – e.g. the use of Key Performance Indicators (KPIs)

could be useful);

ii) To identify the root causes (e.g. by applying 5 Whys);

iii) To develop a solution to improve the systems’ performance (e.g. Kaizen events, Gemba

walks for simple solutions; 8D problem solving, A3 report for more complex).

The necessity of applying Lean tools after the MFCA analysis motivates this study and its validation.

Despite most of this Lean thinking methods were suggested in the first case study; the impact and

performance of these suggestions were not applied during the internship due to production’s layout

modifications and the transition phase of the manufacturing line.

Consequently, this context motivated the proposal of a methodology which integrates the MFCA and

Lean management tools, taking advantage of their complementarities. On the one hand, MFCA aims to

present to the managers the real monetary value of the waste and the QC within the manufacturing

system that has the highest contribution to the waste cost. On the other hand, Lean Management tools

goals are related to physical flow analysis and problem-solving solutions. Thus, arises the research

question: How to integrate MFCA and Lean management tools for continuous improvement system? To

answer this question, an integration methodology is proposed. Further, is validated through its

application to a case study.

44

The present section is organised as follows. Firstly, a conceptual review related to MFCA and Lean

manufacturing tools focused on their complementarities is presented. Then, the proposed integration

methodology is described. In the third subsection, the methodology is applied to a case study of an

injection moulding system, including also the developed improvement solutions. The case study

application aims a preliminary validation of the proposed methodology.

5.1. MFCA and Lean approaches

Currently, in highly competitive markets and unstable economies, most of the companies in the

manufacturing industry face the challenge of increasing profit margins maintaining the levels of product

quality. Moreover, due to environmental concerns, companies have been pressured to increase the

resources’ efficiency of the processes reducing the material wasted and energy consumed. Such factors

are compelling the manufacturing companies to achieve higher productivity levels at the lowest possible

cost while reducing their environmental impact [1]. In the specific case of the injection moulding

companies, the customers (market) is constantly demanding for more complex parts with a higher level

of components/functions integration. The product’s life is decreasing, lowering gains related to economy

of scale and the technologies levelling worldwide tends to diffuse the type and location of competitors.

This introduces a high uncertainty in the business margins; therefore, the minimisation of production

and lead time, and of the resources consumed is a daily concern.

In this industrial framework, the MFCA is considered as a promising approach to tackle these challenges

[1]. According to ISO norm 14051 presented in [3], MFCA is a management tool that fosters the

transparency of energy and material flows and consumptions, through the identification and

quantification in physical and monetary units of the material and energy flows. In consequence, this

method has been developed to support industrial companies for increasing material and energy

efficiency and supporting management decisions. The MFCA evaluates the positive products (the

product) and negative products (waste-considering all types of losses) separately in order to enhance

the inefficiency of material and energy use and to motivate managers to reconsider their strategy

nurturing an increase of production efficiency. Once the waste cost is visible, the improvement

opportunities may be analysed in detail, elaborated and evaluated and – in the case of positive

opportunity – implemented; aiming at the reduction of resources used and, consequently, the reduction

of the overall production cost and environmental impact [32].

As explained in the literature survey, MFCA is a method of cost accounting which sub-divide the entire

production system in QCs: processes/actions/locals where materials are transformed or stocked and

consequently cause an increase in costs. For each QC, firstly, the inputs and output of positive and

negative products are identified. Then, their quantities are measured (physical units) and afterwards

their costs determined (monetary units). The MFCA data obtained during the analysis is presented in a

material flow cost diagram. It shows the allocated cost per QC, individually, of the total production system

or both Figure 5-1 shows schematically a cost related Sankey diagram is evincing its differentiation

between typical cost input items (material, energy, system cost) and outputs (product, waste cost). For

simplification reasons, the waste management cost is neglected. Finally, MFCA allows to understand,

45

not only, the contribution of each QC in the total production cost, but also evidences the influence of

every QC-section (QC- Material; QC- System; QC- Energy) within each QC.

As it can be concluded, the MFCA shows the performance of each QC, through the mapping of

information related to each QC. This information allows the stakeholders to identify critical processes

based only on the monetary aspect not being able to analyse the criticality level of the QC and its

correspondent QC-Section. This is due to the lack of indicators (within MFCA indicators) able to identify

single QC’s and QC-Section’s contributions for the Total Cost, or any parameter above the expected or

the desired value. Naturally, from the MFCA results the stakeholders can do side calculations to have

that information, however the MFCA do not present directly those indicators.

Having performed the calculations of MFCA, it is necessary to develop solutions and implement them.

The literature on MFCA largely neglects strategies for taking advantage of its detailed and monetary

based diagnosis as procedures of critical aspects’ identification and strategies to develop solutions.

Lean has a different approach for diagnosis and critical aspects identification. While MFCA is essentially

a diagnostic tool and is concerned to make “visible” the monetary value of the production waste, Lean

has a more incisive diagnostic supporting the identification of critical processes/tasks, as well as the

root causes, also including problem-solving tools/approaches. Lean approach is divided in diagnostic

tools, as VSM and Gemba Walk which analyse the production system in a macro perspective without a

direct relation to the monetary value of the processes and/or the production cost [33]. Nevertheless,

these analyses aim to identify the critical processes/tasks to launch continues improvement projects

(based on Kaizen principles – Plan-Do-Check-Act). In fact, the main goal of Lean diagnosis tools is to

identify non-value added activities and analyse them. - Plan phase – aiming to eliminate waste

regardless of its nature (8 MUDA [4] presented in Table 5-1).

Product

(total)

QC1 QC2

Material

cost

Energy cost

System cost

Material losses

cost (QC1)

Material losses

cost (QC2) Material losses (total)

Cost of semi-finished product (QC1)

System cost

Energy cost

Figure 5-1 Sankey diagram of a production system

Cost of finished product (QC2)

46

Table 5-1- A general description of 8 MUDA

Type of MUDA Description

Overproduction Occurs when a company produces more than the volume required for the

customer;

Waiting time When people or products have to wait for a work cycle to be complete;

Motion Any unnecessary movement of machines, people or parts, within the process;

Transportation Any unnecessary movement of machines, people or machines, between

processes;

Rework Occurs when a part is not in concordance with the customer specification and

the part need a correction;

Over Processing Processing beyond the customer standard specifications.

Wasted Talent Unused employee creativity as losing time, ideas, skills, improvements.

The action-plan application accomplishes the effective waste elimination – Do phase – where the

problem-solving tools as Kaizen events, A3 Problem Solving and 8D method (Table 5-2) (from Lean and

Kaizen inter-connection) are used to define cooperatively between the company collaborators. The

intrinsic characteristic of these tools leads to the need of data collection tasks in physical units to analyse

the results (sometimes with consecutive Gemba Walks). These results are then shown regarding non-

added value time (inefficiencies), defective parts, wasted movements, excessive transports…. During

these problem-solving methods supporting tools for root-cause identification are used. Namely, 5Whys,

5W+1H, Is/Is not, Fish-bone diagram, Pareto analysis, Correlation Diagrams, Yamazumi diagrams,…,

presented in Table 5-3. Then solutions are generated aiming to eliminate the root-causes, usually using

good-practices of Lean tools like 5Ss, SMED, Kanban, Mizusumashi, among others, presented in Table

5-4.

Table 5-2 Lean Tools description for problem-solving

Problem Solving

Kaizen event

A long-time team workshop with a specific(s) aim(s) for a critical area. Usually, this

type of events is led by a team leader and must include, training, data collection,

discussion and implementation. In the end, the improved results should be

communicated to the managers. [34]

A3 report

This problem-solving tool is based on the Deming Cycle, the PDCA Method. This

report involves all PDCA phases to problem-solving and continuous improvement.

This format is used to communicate all the relevant information efficiently due to its

high visual impact.[35]

8D method A method focused on product and process improvement to identify, correct and

eliminate issues. The 8D establish a correlative action of the problem and origin of

47

the problem. It is performed by following the 8 Disciplines (Plan; Form a team;

Describe the problem; Interim Containment Action; Root cause analysis; Permanent

corrective action; Implement and validate the previous D; Prevent Recurrence;

Closure and Celebration)[36][37]

Gemba

Walks

A walk to observe where the work is happening (shop floor) to analyse in person the

station or workplace, observing where the work is done and discussing the problems

close to the place. This last statement is performed throughout the interaction with

the employee in order to understand why the tasks are done like he does and finds,

as a team, possible solutions.[38]

Table 5-3 Lean Tools description for root cause identification

Root Causes

5Whys The method involves asking "Why?" five times. The purpose is to move beyond the

various aspects of the problem in order to identify the real cause(s).[39]

5W+1H

A method that involves asking four of the W’s (Who?; What?; Where?; When?) and

the one H (How?) and is used to comprehend the details, analyse the inferences

and judgment to get to the fundamental facts.[40], [41]

Is/Is not

The analysis is performed on board with two columns on cover “is” and “is not”. Thus,

questions like What, Where, When and How big is asked about the problem and the

answer is allocated to the relevant “is” and “is not” column.[42]

Fish-bone

Diagram

A diagram also known as the cause-effect diagram is an analysis that breaks the

“whole” problem in “parts”. Usually, the bones are used to indicate the impact of

causes (the bone's size measures the impact) consequently the larger bones close

to the fish’s head represent an activity or skill with big impact.[43]

Pareto

analysis

A technique based on the 80/20 rule. It is an analysis which separates a limited

number of inputs that represents a big impact on the output. This analysis is based

on the idea that 80% of the problems are due to 20% of the causes. Consequently,

this analysis aims to prioritise a range of items which have different levels of

significance by separate the “vital few” from the “useful many”.[43]

Correlation

Diagrams

A plot of points to study and identify the existence of a relationship between two

variables. It is often used in a follow-up to the fish-bone diagram to identify the

possibility of existing more than two variables between cause and effect.[43]

Yamazumi

Diagrams

A stacked bar chart which categorises the processes individually in Value added,

Non-Value added or Waste. The duration of each task is displayed within the

process’s bar chart and each task stacked to represent the entire process.[44]

48

Table 5-4 Lean Tools description for good practices

Good Practices

5Ss

A tool for organising the workplace in a clean, safe and efficient manner to provide

employee’s productivity and to ensure the standardised work. Based on five

Japanese words all beginning with S – Seiri (Organisation – Separate what is

essential from what is not); Seiton (Neatness – arrange the required items in an

orderly manner); Seiso (Cleaning – keep the workstation clean); Seiketson

(Standardization); Shitsuke (Discipline – follow the procedure).[45]

SMED

Single Minute Exchange of Dies is an approach used for reducing quality losses due

to changeovers. This approach is based on the study and the measurement of the

operations and then suppress on-added operations and convert internal into external

setup, thus try to simplify the design of the machine as well as the trials and

controls.[45]

Kanban

A technique that uses printed cards in a plastic cover which contains specific

information usually a product reference, part number and quantity required. The

word Kanban means “card you can see”. It is used to tell a producer what, when and

how much to produce a part.[46]

Mizusumashi

A person who manages all the logistical work of supply components, materials,

auxiliary materials required. This person gives the materials in small and pre-

established quantities in a specific time avoiding the WIP. This practice also helps to

eliminate the waste of transportation. Usually, this work is performed per

experienced workers, they know where the parts needed are storage and can serve

different workstations.[47]

The Kaizen process continues by assessing the impact of the implementation of the solution and by the

comparison between the expected and achieved results. Usually Lean uses the Visual Management

(VM) to access the production performance during the production time. In some cases, the VM displays

KPIs to assess if the action-plan is allowing the performance previously defined. This procedure

corresponds to the Check phase. After that, a beginning of a new procedure standardisation and

identifying the next critical area and (in case) analyse the aspects of the difference between the expected

and achieved results – Act and subsequent Plan phases.

Despite different approaches to identify wastes and achieve better performance of production system,

MFCA and Lean tools have the same aim and starting point: both analyse the production flow in physical

units and present the actual production performance status. However, Lean is mainly concerned about

reducing MUDAS and MFCA is concerned about the waste economic impact and its reduction based on

its cost. (Figure 5-2). On the one hand, MFCA’s goal is to demonstrate the improvement opportunity by

showing the waste cost but is not primarily designed for problem-solving nor to present specific

solutions. On the other hand, Lean management aims at reducing all types of waste and uses the

49

problem-solving methods and Lean tools to identify the root causes and to provide solutions. However,

is not designed to present the results in monetary units – such as MFCA. Consequently, a methodology

to integrate these two approaches is proposed taking advantage of their complementary aspects.

Figure 5-2 - Complementary aspects and integration opportunity

5.2. MFCA-Lean Methodology

The proposed methodology integrates MFCA structured phases with an adaptable application logic of

Lean tools, i.e., the tools should be selected according to with the production issues. It also incorporates

a very important rationale for the effective success of its implementation: the Kaizen continuous

improvement foundations. The Plan-Do-Check-Act cycle is imbibed in the MFCA-Lean methodology

although is not explicitly mentioned in the methodology sequential phases.

The MFCA-Lean Methodology is composed by the following steps:

• Objectives and Scope Definition:

o The company should define the “macro-level” improvement objectives aligned with their

internal strategy. For example, decreasing of human resources, the material waste,

energy consumption, parts out of specification…

• Operational KPIs definition:

o The MFCA- and Lean-based operational performance indicators should be selected

considering the objectives and scope: MFCA KPIs and Lean KPIs;

o The KPIs derived from MFCA are “mandatory”, the one from Lean are more dependent

on the objectives and scope.

▪ When the MFCA-Lean methodology is applied for the first time is possible that

the company does not have the necessary information about the process to

assign a Target Value to a specific KPI.

MFCA Method Lean Management

Calculation Model in monetary units

Motivate managers by presenting the waste

values

Based on physical units

Root-Causes and problem-solving tools

Present the improvement results in physical units

Manufacturing system

characterization in physical units

Increase efficiency by the waste elimination

Continuous improvement

system

50

o The Target Values for each KPI should be defined, according to with the company

strategy.

• MFCA application and data gathering:

o Application of the MFCA method, namely related to QC definition and related data

gathering;

o Additional data gathering related to the information required for the Lean-based KPIs.

• KPI calculation and process mapping

o Development of a calculation method based on the previously defined KPIs, and KPIs

computing;

o Performance mapping by the use of dashboards with KPIs values for each QC.

• KPIs vs Target Values

o Comparison of obtained KPIs values with Target Values to identify:

▪ The critical QCs – the ones contributing more for the total waste cost

▪ The critical KPIs – the ones with values more distant from the target

• Lean tools for continuous improvement

o Establishment of the opportunity of improvement, selected among the critical QCs

and/or KPIs.

o Considering the nature of the problems, analyse and select an appropriate Lean Tool

to increase the process efficiency, and reduce waste and cost (apply problem-solving

methods and Lean good-practice tools).

Thereafter, the solution definition and implementation, the MFCA should be re-applied considering the

Lean modifications and the potentially improved performance should be confirmed. Subsequently, a new

improvement cycle should begin, aiming to promote a continuous improvement cycle by incremental

changes – the application of the Demming Cycle, also known as PDCA, Plan, Do, Check and Act [45].

51

5.2.1. Objectives and Scope Definition

The first step of the integration approach is the definition of the objectives that should be aligned with

the company’s strategical planning. These “macro objectives” should be the translation of the strategic

objectives in operational performance figures. As an example, for the strategic goal “to be an

environmentally friendly company” or “to reduce our foot-print 20% in the next 2 years”. The subsequent

objective of the methodology application could be “reduction of the energy consumption in the production

line A on 10%” (Another example of application objectives can be: increase the added-value per worker,

or per part produced; the reduction of production costs in a specific amount or percentage, etc).

Furthermore, the scope definition will delimit the production system or part of it where the methodology

will be applied: e.g. a single process, a single product manufacturing line, or the whole production

system. The objectives and scope definition will influence the application process of the proposed

methodology.

5.2.2. Operational KPIs definition

The second step of the methodology is the KPIs identification and selection. A KPI is a management

tool which evaluates the business performance considering the company strategy and goals [33]. A

correct KPI definition allows the methodology to identify the critical points and relevant aspects aligned

with the company’s strategy. These KPIs should reveal the current performance regarding the pre-

established objectives.

According to the context of the present dissertation, the connection of the MFCA and Lean logics to

reduce MUDAs and production costs, some KPIs are recommended in the following table.

Table 5-5- KPI recommended for the integration approach and its application

Application KPI Definition

MFCA

Indicators

Final Output

and QC

indicators

Energy

consumption Cost

Monetary value of the energy consumed during the activity

System Cost Monetary value of the system components (machine

depreciation, employees and space) during the activity

Material Stock

Cost

Monetary value of the material stocked during the activity

Product Cost Value in monetary units of the product

Waste Cost Value in monetary units of production waste

Final Output Total Production

Cost

Cost of the total production

Figure 5-3- Overview of the MFCA-Lean methodology

52

Lean

Based

Indicators

Production Lead

Time

Time required to manufacture an item, from release of an

order to the shipment

Total Production

Time Time required for manufacture the entire order

Material rejected Total Material in Kg that is rejected during the production

activity

Rejected parts Total number of products that are rejected by the

production system

Indicator for

QCs

Associated Cost

Monetary value increased by the inputs in each QC,

caused by the energy, system and material consumption

costs.

Setup time and

cost

The time required to prepare an equipment or system to

be ready to start its task and the associated cost.

Waiting time and

cost

The time that people or parts are waiting for the previous

work cycle time to be complete and the associated cost.

Overall Equipment

Effectiveness

identifies (OEE)

The percentage of productive manufacturing time

considering all losses. The OEE calculation is based on

three factors the Availability the Performance and Quality.

The MFCA indicators (Table 5-5) might be unknown on the first time MFCA is applied so that no Target

Values can be defined. The recurrent use of the proposed methodology, in a Kaizen logic, will allow for

the perception of the aimed values for these KPIs. For a further KPI analysis, the Target Value should

be defined having in mind the figures used for the operational objectives. The Target Value definition

supports the proposed methodology since it establishes a milestone or a numerical goal for each KPI

allowing a better comprehension and evaluation of the current state of the company’s performance. The

Lean based KPIs (Table 5-5) are already applied in many businesses for manage and control systems

allowing a direct definition of Target Values for the corresponding KPI.

5.2.3. MFCA application and KPIs calculation

MFCA methodology should then be applied to appraise the production system current situation.

According to the ISO standard 14051 [3], the method application follows a specific and determined

sequence. For the proposed methodology that sequence was respected and additional tasks are

included aiming to calculate not only the MFCA related KPIs but also the Lean related ones. The steps

are defined as follows:

• Engaging Management

o First, the company management should recognise the practicability of the MFCA in

achieving the organisation's goals;

o Then, should provide the necessary information that is required for the analysis;

• Production system characterisation (defined in the scope):

53

o The scope and boundaries defined should be respected. The time period of the analysis

should also be determined– it should be large enough to take into account the process

fluctuations.

• Definition of QC

o The system should be divided into sub processes where the material passes throughout

a transformation process and/or is stocked, such as storage, production units, quality

control, etc..

• Identification of the inputs and outputs for each QC

o For each QC, the inputs and outputs should be defined. For example, the inputs can be

the materials involved in the process and energy required; the outputs can be the

product and material losses which correspond to nonmarketable products.

• Quantification of the material and energy flows in physical units, and additional QC information:

o Data related to the material and energy flows and human resources data should be

collected in physical units.

o Data gathering about QC performance besides material and energy flows, namely setup

time, waiting times, transports, maintenance time, etc.

• Quantification of the material and energy flows, as well as important operations/tasks, in

monetary units:

o The material and energy flows should be converted into monetary units by information

gathered from financial department or similar sources of information;

o The operations or tasks considered relevant to assess, e.g. setup, waiting,

maintenance, etc., should also be converted to monetary units.

The regular application of a MFCA analysis demands a calculation model to support the organisation to

understand the real waste cost and the consequences of the material used and lost. This calculation

model’s output presents only the “mandatory” MFCA KPIs, thus for the MFCA-Lean methodology, an

output/dashboard modification was performed. This modification allows the stakeholders to analyse

directly from the dashboard the production performance. Those dashboards are presented in detail in

the next section.

54

5.2.4. Process mapping: KPIs vs Target Values

At this point the current state of the production system is well-known, and the results can be analysed.

Aiming to facilitate the overall systems performance two types of dashboards are proposed (Figure 5-4),

one for each QC and the other showing the total performance of the system. Both dashboards suggested

have two main areas, one dedicated to the MFCA indicators, the other to the Lean indicators. Also, they

have a column which connects each KPI with the Target Value, e.g. by showing the direct ratio between

these two figures. Nevertheless, other metrics can be used by the company. The QC dashboard has

more detailed information related to specific operation or tasks, if existent, e.g. setup, waiting time, etc.

This dashboard also shows the contribution of each QC to the overall production cost. The dashboard

related with the total performance has the final MFCA typical indicators of performance as well as the

total cost involved. The contrast between the KPIs observed, and the Target Values indicates the current

state of the process where improvement opportunities might be visible.

Figure 5-4 A proposal of QC and Total Production System dashboards output data, the comparison with Target Values and the performance indicators.

KPI and TV

discrepancy Lean KPIs

Auxiliary data for KPI calculation

MFCA

MFCA

Lean KPIs

Auxiliar data

55

5.2.5. Critical QC and KPIs identification and Lean tools

application

Then, the determination of the critical QC and the critical KPIs can be made by the analyst or the team

through the observation and analysis of the dashboard. Several strategies can be followed,

nevertheless, in the present work is suggested the following.

• Identify the KPIs with “higher distance” to the Target Values, and consider them as critical;

• Identify the QC(s) with higher “QC associated cost” KPI and consider it(them) critical even

though the distance to the Target Value is small;

• Identify in the critical QC(s) the KPIs that most contribute to the bad performance (waste-, time-

, energy-related) and consider it as critical.

The selection of the critical QCs and KPIs allow on efficient and effective subsequent phases of root-

cause analysis, and solutions development and implementation. As proposed by the Kaizen philosophy,

the continuous improvement process should be accomplished by a step-by-step approach, launching

“only” a localised project with very specific objectives at the time.

Hence, the critical QC or QCs must be analysed in detail to understand the reasons behind the crucial

aspect through the application of the Lean diagnostic tools already mentioned. Therefore, an

improvement strategy can be defined through the appropriate problem-solving method. Finally, the Lean

tools for continuous improvement should be performed and the improvement results confirmed. For

example: If the issue is related with the OEE, then Availability, Performance and Quality performance

should be analysed. Moreover, If the problem is related to quality related KPI, the 5Whys method should

be used to achieve the root cause(s) for defective products and Kaizen events, A3 report or 8D problem-

solving methods should be applied. Furthermore, if the issue is related to the setup time KPI, the SMED

and 5s Lean tools can be implemented to eliminate wastes that result from a non-organized work area

or even to convert the internal activities to external and eliminate non-essential operations creating a

standardized setup work; if the critical KPI is related with the waiting time an A3 report or 8D method

can be developed to minimize waiting times.

Concluding, a Kaizen based strategy provided by the application of Lean tools should be performed,

and the improved results should be analysed by the reapplication of the proposed integrated

methodology.

5.3. MFCA-Lean Methodology application

This section presents the MFCA-Lean methodology application and is organised as follows. First, a brief

characterisation of the production system is presented, followed by the presentation of the objectives

defined by the company and the KPI selected for the study. Thereafter, the methodology for the

application of MFCA is presented, and the calculation model explained. Subsequently, the analysis of

the obtained results through the application of the MFCA is presented, followed by the KPI and Target

56

Values analysis. Finally, the solutions suggested, and the improvements achieved from to the application

of the Lean improvement solutions are described and discussed.

5.3.1. Production system and product characterisation

The production system selected to validate the methodology presented was developed in the same

injection moulding company as the first case study. Consequently, all the steps related to MFCA

collecting data are the same as presented in detail in section 4. The production is characterised by being

a Make-To-Order production which has been characterised in section 3. In contrast with the previously

presented case study, this production has not dedicated employees and machines/equipment.

Consequently, the system cost allocation follows a different perspective which is shown in the following

sections.

The manufacturing process was already described in section 3, thus only a brief description is

presented. The production process in study is divided into four main steps. The first is the Injection

Moulding process where the raw material is transformed into final product, then the product is subjected

to a quality analysis and then packed. Afterwards, the product is packed and stored until the client

delivered.

To understand the calculation model and the methodology application the characteristics of the product

are presented in Table 5-6, as the moulding’s constituents, the respective weight and the expected

duration of each cycle, as well as the total production volume. For confidentiality reasons only, the

necessary values are presented, and the part configuration cannot be displayed.

Table 5-6 – General dimensions of the production process and product

Units Weight

Parts per moulding 4 parts 2.12 g/part

Runners per moulding 1 4.1g/moulding

Production lot size 36000

Theoretic cycle time 12.3 sec/ moulding

The methodology applied to the production system is present in the next section.

5.3.2. Objectives, Scope and Operational KPIs Definition

The starting point is the objectives and scope definition. Therefore, the company defined as its main

goal the increase of profit and the reduction of material, energy and human resources. Then, the scope

was defined as the entire process from the material supply until the product delivered.

The next step of the methodology is the definition of the appropriate KPIs. Table 5-7 presents the

appropriate KPIs to analyse the current state of the production system considering the company’s

57

objectives. Since one of the objectives defined was increase the gain margin, the Total Production Cost

was selected as KPI to confirm and evaluate the actual cost. Then, considering the second goal, the

material reduction, the waste material was selected to provide the current performance to evaluate the

deviation between the real value and the expected to appraise improvement possibilities. To evaluate

the possible reduction of human and energy resources and its impact three different indicators were

selected: i) the Total System since the human resources cost is included on it; ii) the OEE which evaluate

the equipment performance and availability that is related to the energy consumption and labour’s work

duration due to the production time; iii) and the Set-up time which analyse directly the labours and

equipment occupation during a period that no product is produced.

The following phase is the Target Value definition/attribution presented in Table 5-7. This value can vary

according to the production characteristics. For this particular case, there is not yet Target Value for the

total production cost and for the total system cost because it was the first time the MFCA was applied.

For the total amount of material waste, the 3% of Target Value represents an average value aimed by

the company, including the material wasted due to discharges, material needed for replacement and

parts needed for the quality control destructive test. The definition of the Target Value for Set-up time

was based on an estimated value that has resulted from company’s previous study. The OEE is defined

based on the company experience, at this point the company aims to achieve at least 65%. This value

represents what they consider as a reasonable value for this parameter.

Table 5-7 – Key Performance Indicators to evaluate the performance considering the company’s goals.

Objective KPI Target Value

Increase the profit

Total Production Cost Undefined

% Material Waste <3%

Reduce the resources uses

Total System Cost Undefined

OEE >65%

Setup time <1h30min

The Target Values presented in Table 5-7are used to evaluate the current state of the production system

based on the aimed results it will support the Check phase of the cycle. This evaluation is presented in

the methodology dashboards for final results, section “KPI and TV discrepancy”.

The following section presents the method applied, and the calculation model developed based on the

information submitted above.

5.3.1. MFCA application and data gathering

To perform MFCA analysis, the steps presented in section 4 were followed. Firstly, the data collection

period was established as one production bunch, i.e. the time required to produce the total order (36

000 good parts). Then, the production system was sub-divided in QC, and the material flow was

58

analysed. Figure 5-5 illustrates a material flow map, where the QC are identified as well as the inputs,

positive product and negative product flows.

Once defined the QC, the inputs and outputs should be quantified in physical units. As explained before

each quantity centre identifies three different parameters, namely, the Material Stock, the Energy

consumption and the System. Consequently, the material consumption and energy were measured. On

the one hand, the material used was weighted and, on the contrary, the energy consumed was measured

directly from the machines. Then, the parameters of the third component, equipment and human

resources, were allocated by the total dedicated time to this particular production.

To analyse the MFCA inputs and outputs in physical units, an extensive data is required about the

following aspects:

• Raw Material – The amount of in Kg and the operating materials used in each QC.

• Material Stock – The amount of the material which is stored in each QC in Kg;

• Energy Consumption – The amount of energy consumed by each machine in each QC in KW

and subsequently the total working hours

• System:

o The employees - The total time for each employee/ leader and Project Manager

dedicated to the production to allocate its cost to each QC.

o The space – The total space in square meters required by the production (space

occupied by the machine; the packaging; the Raw Material…) allocated to each QC.

o The Equipment – The total time that the equipment was occupied for the current

production to allocate its cost to each QC.

Thus, is necessary to define a cost allocation criterion for each type of cost: material, energy and

system, these allocations are described in the next section.

Input

Raw material

area

Hopper dryer Injection

Machine

Packagin

g

Quality

Control

Final Product

Warehouse

Waste management

Product

Waste

Input Material flow

Positive product flow

Negative product flow

MFCA boundary

Figure 5-5- Material Flow model

59

5.3.2. Energy, System and Material cost calculation

For the present production system, the Energy and Material cost quantification in monetary units follows,

not only, some of the criterion used for the previous study, but also the procedures developed to collect

the data. That can only be applied due to the processes similarities. Both products are produced through

an injection process and also the Equations used for the previous chapter’s cost calculation retracts the

reality of the present study. However, due to the production strategy the quantification system cost must

be adapted, and the production time is considered as a variable.

Energy Cost

The Energy cost is calculated through two steps. First the power consumed is measured, and the energy

required calculated using Equation (4.5). Then, the Energy cost is calculated by the Equation (4.6),

where is considered the energy consumed by the production system and the energy cost per kilowatt-

hour.

System Cost

The System cost is defined as being the sum of all expenses incurred during the production system,

namely the employee cost, the space cost and the equipment cost. Thus, it is calculated through the

Equation (4.7) presented in the previous chapter.

Employee’s Cost

The present production has not dedicated employees so each employee can have different tasks and

can be involved in different QC. To evaluate the contribution of each employee to the correct QC the

procedure described in section 4.3 is followed. Thus, a time distribution was performed considering the

total dedicated time within the production system (Table 5-8)

Table 5-8- Percentage distribution of employees per QC.

QC Project

Manager

Leader Leader

Assistant

Worker Warehouse

Employee

Raw Material 2% 8% 2%

66%

Hopper Dryer 1%

92%

Injection Machine 60% 92% 6% 5%

Quality Control 17.5%

Packaging 17.5%

93%

Final Product

34%

Waste Management 2%

2%

100% 100% 100% 100% 100%

The Project Manager and Leader allocation costs are calculated using Equation (5.1), where the

𝑐𝑜𝑠𝑡𝑝𝑟𝑜𝑗𝑒𝑐𝑡 𝑚𝑎𝑛𝑎𝑔𝑒𝑟 is the project manager or Leader cost per hour, the 𝑁𝑟 𝑜𝑓 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛𝑠 is the number of

manufacturing systems that they are responsible for and the 𝑡𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 is the total production time.

60

Then, the Leader assistant, worker and warehouse employee allocation costs are obtained by Equation

(5.2), where 𝑐𝑜𝑠𝑡𝑒𝑚𝑝𝑙𝑦𝑒𝑒 is the employee cost per hour, the 𝑡𝑒𝑚𝑝𝑙𝑜𝑦𝑒𝑒 the time in hours spent by each

employee to the QC, and 𝑁𝑒𝑚𝑝𝑙𝑦𝑒𝑒𝑠 is the number of employees involved in a particular activity related to

the QC.

𝑃𝑟𝑜𝑗𝑒𝑐𝑡𝑚𝑎𝑛𝑎𝑔𝑒𝑟

𝐿𝑒𝑎𝑑𝑒𝑟𝑐𝑜𝑠𝑡[€] =

𝑐𝑜𝑠𝑡𝑝𝑟𝑜𝑗𝑒𝑐𝑡 𝑚𝑎𝑛𝑎𝑔𝑒𝑟/𝑙𝑒𝑎𝑑𝑒𝑟 [€/ℎ]

𝑁𝑟 𝑜𝑓 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛𝑠 × 𝑡𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 [ℎ] (5.1)

𝐸𝑚𝑝𝑙𝑦𝑒𝑒 𝑐𝑜𝑠𝑡[€] = ∑ 𝑐𝑜𝑠𝑡𝑒𝑚𝑝𝑙𝑦𝑒𝑒 [€/ℎ] × 𝑡𝑒𝑚𝑝𝑙𝑜𝑦𝑒𝑒[ℎ] × 𝑁𝑒𝑚𝑝𝑙𝑦𝑒𝑒𝑠 (5.2)

Space’s and Equipment’s Cost

Space and equipment costs are calculated using Equations (5.3) and (5.4) respectively. The Space cost

is assigned to each QC individually based on the space required to perform the activities involved as

well as the space occupied by the equipment. Regarding that, the 𝑆𝑝𝑎𝑐𝑒−𝑄𝐶 is the space occupied by the

QC in square meters; the 𝑇𝑜𝑡𝑎𝑙 𝑆𝑝𝑎𝑐𝑒 is the total area rented in square meters; the 𝑅𝑒𝑛𝑡 𝐶𝑜𝑠𝑡 is the value

paid for the total area per hour, and the 𝑡𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 is the total production time in hours. Then, as presented

in section 4.3 the equipment cost is calculated based on the type of equipment (dedicated or non-

dedicated) for non-dedicated equipment the equipment cost is calculated using Equation (4.12)

considering the allocation criterion, Equation (4.11). Then, for dedicated equipment the Equipment cost

is allocated considering the 𝐸𝑞𝑢𝑖𝑝𝑚𝑒𝑛𝑡 𝑐𝑜𝑠𝑡 per hour that corresponds to the depreciation or rent value

per hour of the equipment required in each QC.

𝑆𝑝𝑎𝑐𝑒 𝑐𝑜𝑠𝑡−𝑄𝐶[€] =𝑆𝑝𝑎𝑐𝑒−𝑄𝐶 [𝑚2]

𝑇𝑜𝑡𝑎𝑙 𝑆𝑝𝑎𝑐𝑒 [𝑚2]× 𝑅𝑒𝑛𝑡 𝐶𝑜𝑠𝑡[€/ℎ] × 𝑡_𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛[ℎ] (5.3)

𝐸𝑞𝑢𝑖𝑝𝑚𝑒𝑛𝑡 𝑐𝑜𝑠𝑡−𝑄𝐶[€] = 𝐸𝑞𝑢𝑖𝑝𝑚𝑒𝑛𝑡 𝑐𝑜𝑠𝑡 [€/ℎ] × 𝑡𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛[ℎ] (5.4)

Material Cost

The Material cost for this production system is calculated using Equation (4.13). Moreover, the Injection

machine QC in this case study has a particularity which is a consequence of the mould design. The

mould used for manufacturing this product produces four parts and one runner. The runner is a waste

considering the MFCA rules/principles since it causes system and energy resources consumption.

Consequently, the allocation criterion for the waste components in the QC corresponds to the total

amount of material loss (7.37% of defective parts and 30.21% to the runner’s production for the

manufacture of 36028 right parts).

Output allocation

The material, energy and system costs were allocated to the output product and waste in the same way

presented in section 4. The energy costs allocated to the material loss are associated with the production

of defective parts, i.e., the energy consumed in each quantity centre is assigned to the output flow by

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the percentage of the total production that corresponds to product and material losses. For example, in

the Injection Machine, Table 5-9, 37.58% of the energy resources is considered waste because this

percentage corresponds to the material used to produce defective parts and for the runner produced

which is mandatory for the production of good parts. The same logic is followed for the Space and

Material allocation to Product and Waste.

Table 5-9- QC-Injection Machine

Output

Product 390.34 € Waste 237.58 €

% € % €

Inp

ut

Previous QC 509.41 € 62.42% 317.96 € 37.58% 191.45 €

Operating Materials 2.55 € - % - € 100.00% 2.55 €

Stock - € - % - € 100.00% - €

System 100.39 € 62.42% 63.69 € 37.58% 38.35 €

Energy 13.92 € 62.42% 8.69 € 37.58% 5.23 €

The Equations presented above were applied to each QC to develop a calculation model presented in

the next subsection.

5.3.3. Calculation model

The calculation model development was obtained by the combination of the typical MFCA calculation

model, presented in section 4, and the KPI defined, shown in Table 5-7.

The original MFCA calculation model integrates the information related to costs and material flows data

and has as outputs the monetary value of the product and the waste separately, to evaluate the

economic state of the manufacturing system. The MFCA-Lean methodology adds to the original

calculation model the necessary and relevant information in physical units to evaluate the operational

performance through the KPIs analysis of the production system. The following steps present the

calculation process of the model:

9. Material

a. Calculate the main material input in the 1st QC, in Kg and €.

b. Characterize the input and output of each QC by the proportion of positive and negative

product quantities and identify in physical units those quantities

c. Detect and calculate the operating material involved and assign them to the correct QC.

10. Energy

a. Calculate the energy cost and energy consumption of each equipment in each QC in €

and kW respectively.

b. For the present work, the energy cost and consumption were allocated the energy cost

and consumption by the proportion of positive and negative product quantity.

62

11. System

a. Calculate the cost of time spent by each employee in each QC.

b. Calculate the cost of the space needed for the production

c. Calculate the equipment cost during the production

d. Allocate the system cost as the same way as energy cost.

12. Calculate the product and waste costs for each QC

5.3.3.1. KPI calculation

After the MFCA application, the MFCA-Lean methodology next step is the KPI calculation and the

correlation criterion selection to incorporate in the original MFCA calculation model. The present

subsection presents the KPI calculation for QC and for the Total Production System as well as the

criterion selected to compare the KPIs and the correspondent Target Value.

5.3.3.1.1. KPI selection and calculation for QC

Considering the objectives exposed above, different types of evaluation can be selected. The first step

is the calculation of each KPI of each QC. For the QC analysis was selected four cost related and two

operational KPIs. Three of the cost related KPI appraise the contribution of each QC-Section within the

total QC Associated. This evaluation allows the stakeholders to recognise the impact of resources

consumption. Thus, the Material, Energy and System contribution are calculated using

Equations(5.5);(5.6);(5.7) respectively. The fourth KPI cost related presents the contribution of the QC

within the Total Production. This evaluation allows the identification of the QC that most contribute to the

Total Production and is calculated using Equation 5.8.

𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙𝑐𝑜𝑛𝑡𝑟𝑏𝑢𝑡𝑖𝑜𝑛𝑄𝐶=

𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙 𝑆𝑡𝑜𝑐𝑘 𝑐𝑜𝑠𝑡

𝑄𝐶 𝐴𝑠𝑠𝑜𝑐𝑖𝑎𝑡𝑒𝑑 𝑐𝑜𝑠𝑡(5.5)

𝐸𝑛𝑒𝑟𝑔𝑦𝑐𝑜𝑛𝑡𝑟𝑏𝑢𝑡𝑖𝑜𝑛𝑄𝐶=

𝐸𝑛𝑒𝑟𝑔𝑦 𝑐𝑜𝑠𝑡


𝑆𝑦𝑠𝑡𝑒𝑚𝑐𝑜𝑛𝑡𝑟𝑏𝑢𝑡𝑖𝑜𝑛𝑄𝐶=

𝑆𝑦𝑠𝑡𝑒𝑚 𝑐𝑜𝑠𝑡


𝑄𝐶𝑐𝑜𝑛𝑟𝑖𝑏𝑢𝑡𝑖𝑜𝑇𝑜𝑡𝑎𝑙𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝐶𝑜𝑠𝑡 =𝑄𝐶 𝐴𝑠𝑠𝑜𝑐𝑖𝑎𝑡𝑒𝑑 𝑐𝑜𝑠𝑡

𝑇𝑜𝑡𝑎𝑙 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝐶𝑜𝑠𝑡(5.8)

The two operational KPI selection was explained before in subsection 5.3.2. The setup time is measured

and expressed directly in the output dashboard in hours, and the OEE is obtained using Equation (5.9).

The OEE calculation is based on three factors, the Performance, obtained by Equation (5.10), the

Availability, calculated by Equation (5.11) and Quality, obtained using Equation (5.12).

𝑂𝐸𝐸 = 𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 × 𝐴𝑣𝑎𝑖𝑙𝑎𝑏𝑖𝑙𝑖𝑡𝑦 × 𝑄𝑢𝑎𝑙𝑖𝑡𝑦 (5.9)

𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 =𝐼𝑑𝑒𝑙 𝐶𝑦𝑐𝑙𝑒 𝑇𝑖𝑚𝑒 × 𝑇𝑜𝑡𝑎𝑙 𝐶𝑜𝑢𝑛𝑡

𝑃𝑙𝑎𝑛𝑛𝑒𝑑 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑇𝑖𝑚𝑒 − 𝑆𝑡𝑜𝑝 𝑇𝑖𝑚𝑒(5.10)

𝐴𝑣𝑎𝑖𝑙𝑎𝑏𝑖𝑙𝑖𝑡𝑦 = 1 −𝑆𝑡𝑜𝑝 𝑇𝑖𝑚𝑒

𝑃𝑙𝑎𝑛𝑛𝑒𝑑 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑇𝑖𝑚𝑒(5.11)

63

𝑄𝑢𝑎𝑙𝑖𝑡𝑦 =𝐺𝑜𝑜𝑑 𝑜𝑢𝑡𝑝𝑢𝑡 [𝑝𝑎𝑟𝑡𝑠]

𝑇𝑜𝑡𝑎𝑙 𝑝𝑟𝑜𝑑𝑢𝑐𝑒𝑑[𝑝𝑎𝑟𝑡𝑠] (5.12)

The KPIs selected and its calculation for each QC is further used for the evaluation of the production

performance, it allows the stakeholders to recognise if the results obtained met with the expected. The

analysis of the contribution of each QC-section and the OEE is then presented in the dashboard Figure

5-4), “Lean KPIs” and the calculation of the OEE factors is presented in the dashboard (Figure 5-4)

section “Auxiliary data for KPI calculation”.

5.3.3.1.2. KPI selection and calculation for Total

Production System

The cost related KPIs (Material, Energy and System contribution) follows the same approach as the

defined for the QCs. Thus, the cost contribution for the Total Production system is calculated using

Equations (5.13); (5.14); (5.15). Then, were added two KPI only for the Total Production System, the

Material Waste to evaluate the total amount of material lost in physical units and the Defective products

to analyse the amount of parts rejected within the total production volume. The calculation of these KPI

is performed using the Equations (5.16);(5.17) respectively.

𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙 𝑐𝑜𝑛𝑡𝑟𝑏𝑢𝑡𝑖𝑜𝑛𝐹𝑃=

𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙 𝐼𝑛𝑝𝑢𝑡 𝑐𝑜𝑠𝑡

𝑇𝑜𝑡𝑎𝑙 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑐𝑜𝑠𝑡 (5.13)

𝐸𝑛𝑒𝑟𝑔𝑦𝑐𝑜𝑛𝑡𝑟𝑏𝑢𝑡𝑖𝑜𝑛𝐹𝑃=

𝐸𝑛𝑒𝑟𝑔𝑦 𝑐𝑜𝑠𝑡

𝑇𝑜𝑡𝑎𝑙 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑐𝑜𝑠𝑡(5.14)

𝑆𝑦𝑠𝑡𝑒𝑚𝑐𝑜𝑛𝑡𝑟𝑏𝑢𝑡𝑖𝑜𝑛𝐹𝑃=

𝑆𝑦𝑠𝑡𝑒𝑚 𝑐𝑜𝑠𝑡

𝑇𝑜𝑡𝑎𝑙 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝐶𝑜𝑠𝑡(5.15)

𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙 𝑊𝑎𝑠𝑡𝑒 =𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙 𝑊𝑎𝑠𝑡𝑒

𝑀𝑎𝑡𝑒𝑟𝑖𝑎𝑙 𝐼𝑛𝑝𝑢𝑡(5.16)

𝐷𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠 =𝐷𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠

𝑇𝑜𝑡𝑎𝑙 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 (5.17)

5.3.3.1.3. KPIs vs Target Values

The present study has four Target Values defined by the managers presented in subsection 5.3.2. To

evaluate the production performance by the correlation between the system’s KPIs and the

correspondent Target Value two evaluation criteria were defined based on the KPI nature. The direct

ratio between the Target Value and the KPI was selected to appraise the variation of the Total Production

Time, using Equation (5.18), and the Setup time, by Equation (5.19). The correlation criterion to calculate

the discrepancy of the OEE and the defective products was the difference between the values

(percentage points), using Equation (5.20) and Equation (5.21). Since the OEE and the Defective parts

are a percentage number, this criterion makes the discrepancy more perceptible.

𝑇𝑜𝑡𝑎𝑙 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑇𝑖𝑚𝑒𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 =𝑇𝑜𝑡𝑎𝑙 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑡𝑖𝑚𝑒𝑇𝑉

𝑇𝑜𝑡𝑎𝑙 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑡𝑖𝑚𝑒𝑅𝑒𝑎𝑙

(5.18)

64

𝑆𝑒𝑡𝑢𝑝 𝑡𝑖𝑚𝑒𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 =𝑆𝑒𝑡𝑢𝑝 𝑡𝑖𝑚𝑒𝑇𝑉

𝑆𝑒𝑡𝑢𝑝 𝑡𝑖𝑚𝑒𝑅𝑒𝑎𝑙

(5.19)

𝐷𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 = 𝐷𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠𝑅𝑒𝑎𝑙 − 𝐷𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑠𝑇𝑉 (5.20)

𝑂𝐸𝐸𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 = 𝑂𝐸𝐸𝑅𝑒𝑎𝑙 − 𝑂𝐸𝐸𝑇𝑉 (5.21)

The information presented above as well as the necessary outputs to calculate the Lean related KPIs is

organised in each QC column as previously presented in subsection 5.2.4 - Figure 5-4

5.3.4. Critical QC and KPIs identification

The analysis of results and identification of critical QC and KPIs is performed based on the methodology

dashboard (Figure 5-4). It describes, not only, the costs per QC (input; output, product and waste) and

per QC-section as the original MFCA, but also, presents the actual performance of the process by the

KPIs presentation. Moreover, this MFCA-Lean dashboard presents also the discrepancy between the

KPI and the Target Value. Allowing the user to evaluate if the pre-defined plan was being fulfilled as

planned. These properties make the MFCA-Lean dashboard more extensive than the original MFCA

flow map and more detailed and objective than Lean analysis.

65

From the analysis of the obtained dashboards, it is possible to find the critical KPIs which allow the

identification of improvement opportunities. To perform that evaluation the analysis of different

categories proposed in section 5.2.5 is followed. For this specific case-study the KPI that presents the

highest distance to the TV were considered more appropriate for the analysis per QC; QC which has

Product Flow

Material Waste Flow

Figure 5-6 – Methodology dashboard for the production system per QC

Figure 5-7 Methodology general dashboard of Total Production System

66

the highest contribution to the Total Production cost and also the KPI which influences this contribution.

For the analysis of the TPS was also considered that an evaluation of the QC that most contributes to

the Total Production Cost was appropriate to assess the critical sub-section. Once performed a visual

analysis of the dashboard obtained, the results were compiled in a matrix for further analysis. This matrix

is organised considering the KPI, the associated cost of each KPI and the criticality level which in turns

evaluated using a colour system. The system colour is divided in two, the red highlight the most critical

value in terms of cost and percentage, and the yellow the second more critical. For each selection

category, the matrix presents the two worse performances, showing the two more critical parameters.

(Table 5-10)

Table 5-10 Identification of critical QC and KPI (per QC and TPS)

The matrix (Table 5-10) is an important MFCA-Lean methodology output: it allows some important

analyses, namely the identification of the QC and KPI critical. The study of this results is dependent on

the analysis and objective of the MFCA-Lean methodology user. In this case, the analysis performed by

the production system in the study is presented per QC and for the Total Production.

Per QC

• The Total Production Time is the KPI with the highest deviation to the respective TV. This

corresponds to 12 perceptual points more than the expected value which represents more than

74.01€ of the production costs;

• The QC with the highest associated cost is the Injection Machine. This QC represents 54% of

the Total Processes Cost that corresponds to almost 116€. It is followed by the QC -Packaging

that represents 33 perceptual points.

• The KPI that contributes more to the QC- Injection Machine is the Material Waste which

represents 37.58 perceptual points of the production which is translated in 237.58€.

For Total Production System:

• The KPI that has the highest contribution to the Production system cost is the Material Input

representing 72.4 perceptual points of the total costs, i.e. 515.37€.

67

From the evaluation of the Total Production System is possible to assess that this value comes in part

from the material wasted throughout the production system, 37.58%. However, 30.21% of that value

corresponds to a manufacturing condition and is mandatory for the manufacturing process.

Consequently, the percentage of material losses, which are a consequence of the runner production to

produce only the good parts, is considered as a material loss for the MFCA application but is a necessary

loss for the process. If the runner’s material were considered as required input, the amount of wasted

material would decrease to 7.37%. The meticulous analysis of the material’s waste nature shows that

within this 7.37%:

• 0.08% is related to the material replacement due to changes in production order;

• 2.41% represents discharges of material after setup;

• 4.88% comes from the production of defective parts and parts destroyed due to the destructive

quality control test.

To evaluate the improvement opportunity related to the material consumed, the analysis of the financial

impact of replacing the cold runner system by one with hot runners is suggested (used in production

system exposed in section 4). However, this evaluation is not part of the dissertation objectives, for that

reason the System cost is recognised as the critical KPI for this subject.

The re-evaluation of the Total Production System results identifies as critical the System contribution for

the entire production costs. Table 5-11 presents the input of each QC-system per QC within the System

cost of the Total Production System allowing the recognition of the QC that contributes more to the total

System costs.

Table 5-11 The contribution of each QC-System within the Total System Cost

System Cost %QC within Total

System Cost

Raw Material Area 3,73 € 2%

Hopper Dryer 5,53 € 3%

Injection Machine 100,40 € 56%

Packaging 53,14 € 30%

Quality Control 14,40 € 8%

Final Product Warehouse 3,48 € 2%

Waste Management - 2,74 € -2%

Total 177.95 € 100%

The analysis of Table 5-11 shows that the critical QC is the Injection Machine which represents 56% of

the total system cost, i.e. 100,40 €, followed by the QC- Packaging that is 30% of the total system costs.

Attempting that the QC Injection Machine and Packaging are also pointed as critical once are the QCs

with the highest associated cost, Table 5-10. Consequently, a root cause analysis should be performed

to these two QCs and the most critical must be selected for further analysis.

68

The Total Production Time, which is pointed as critical in Table 5-10 it is, not only, dependent on the

manufacturing time but also takes into account the Setup time (also pointed as critical KPI). For that

reason, it may be relevant the further analysis.

5.3.5. Lean application tools

The present section aims to reduce the KPIs which were considered as critical in the previous analysis

throughout the application of Lean tools. Considering the previous critical KPI and QC identification, a

different analyses were performed to each KPI considered critical to access the Root-Causes and then

possible solutions. This subsection is organised as follows. Firstly, a root-cause analysis is performed

to access the reason behind the critical KPI. Then, the most critical or the KPI that has the highest

influence on the Production System Cost is selected to further analysis. Finally, the Problem-Solving

solutions were applied and the MFCA-Lean methodology results confirmed.

5.3.5.1. Lean Root-Cause tools application

In the previous section was suggested that the QC- Injection Machine and the QC-Packaging were the

QC that has the highest contribution for the QC-System of the Total Production System. Thus, a root-

cause analysis was performed to these two QC using the 5Whys and 5Ws diagnostic tools.

Table 5-12 presents a detailed analysis of the system costs distribution for the critical QCs to support

the root-cause analysis presented above.

Table 5-12 Comparison value between System cost of Packaging and Injection Machine processes.

QC-Packaging QC- Injection Machine

Labour (total) 52,27 € 51,62 €

Responsible 2,70 € 9,26 €

Leader - € 16,30 €

Employee 49,56 € 2,66 €

Leader supporter - € 23,40 €

Space (total) 0,06 € 1,70 €

Equipment (total) 0,82 € 48,72 €

Total Process’s System Cost 53,14€ 102,04€

69

For QC-Injection Machine: Combined 5Whys and 5Ws for root-cause analysis Figure 5-8.

Figure 5-8 Root-cause analysis to the QC-Injection Machine

From the 5Whys analysis (Figure 5-8) is possible to conclude that the root-cause of the QC-System high

value in the Injection Machine is due firstly the equipment and labours involved in the process. However,

when the root-cause is analysed in detail is accessible that the Equipment value is a consequence of

the machine depreciation. However, the Labour cost is divided in Project manager (18%), Team Leader

(31.6%), Employee (5.1%) and Leader supporter (45.3%) (Table 5-12). As explained in chapter 3 the

Leader supporter main tasks are related to setup activity and the raw material supply. Hence, the root-

cause continuous to understand the reason behind that. Thus, the specialisation level required to

perform the setup activity is directly related to his hour cost. Moreover, the setup activity is also pointed

as the second more critical concerning about the KPI Target Value discrepancy (Table 5-10). Based on

the previous description, the setup is considered the root-cause of the QC-Injection Machine contribution

for the Total System Cost.

Why?

Root-Cause

Because of the Equipment and the Labours involved in this QC.

Why? Because is the QC with the highest resources consumption

The QC-Injection Machine is the 1st QC that contributes more for the TSC Why?

Why?

Because Injection Machine and

the mould are equipment’s with

expensive depreciations

Because this QC involves four

different levels of employees

Root-Cause

Which employee has the

highest contribution for

the labour’s cost??

Leader Supporter

Why?

Because he is a specialized

What does he do?

He performs the Setup Root-Cause

Statement

70

For QC-Packaging: 5Whys Root-cause analysis for System cost in QC-Packaging, Figure 5-9.

From the 5Whys analysis is possible to access that the contribution value which comes from the QC-

Packaging is related to the time spent by the employee to perform that task. The packaging activity has

specific requirements from the quality department, and the operator needs to perform these tasks

following the procedure. Since QC-Packaging is dependent on the quality requirements and that the

most critical QC has an operational cause. The QC-Injection Machine more specifically the Setup can

be improved by the application of a specific Lean tool this parameter is selected for further analysis.

For the Total Production Time:

The last critical KPI to be evaluated is the Total Production Time. To appraise the root-causes of this KPI

a cause analysis based on 5Whys is performed and presented in Figure 5-10. The first two causes are

related to the mould condition, and the third is related to Setup time. The setup time influences the Total

System time since this last is dependent on the manufacturing time but also takes into account the Setup

time which can be improved by the application of problem-solving solutions.

Labour is the sub-section of the QC-System in the QC-Packaging with the highest value. cost.

Why?

Because the packaging phase is the phase that the labour spends most of the time.

Why?

Because the product is packaged in concrete boxes that need to be tagged and this

work is performed by the employee.

Root-Cause

The QC-Packaging is the 2nd QC that contributes more for the Total System Cost Why?

Figure 5-9 Root-cause analysis to the QC-Packaging

71

Figure 5-10 Root-cause analysis to the Total Production Time

Based on the previous analysis is possible to conclude that a reduction of the setup time will reduce its

costs contribution leading, not only, to a positive result in the Labour component of the QC- System

within the injection machine, but also, to a positive impact in the Total Production Time. Thus, if the Total

Production Time is reduced, the cost contribution of the space and equipment would also be reduced.

Regarding these assumptions, the Setup time is selected as a parameter to be analysed carefully as an

improvement opportunity point.

As a primarily conclusion, the MFCA-Lean methodology allows the identification of the critical QC based

on the company's goals. Moreover, without the root-cause analysis performed through the application

of Lean tools, the root-causes of this production issues were not directly identified with the MFCA

application to the production system. Figure 5-11 presents a summary information analysis of the

present subsection to provide a clear idea about the influences

Root-Cause

Root-Cause

Why?

Why?

Production system worked

with a cycle time higher

than the expected

Overproduction: +2004

than the expected

Why?

Setup Time

Because the mould was

achieving the maintenance

time. Thus, some parts were

produced with defects.

Adding, considering the real

cycle time, 2.49 hours and

considering the ideal cycle

time 2.44 hours

Why?

Because it takes more 1.72

hours than the expected.

Why?

Total Production Time is higher than the expected

Why?

Because the mould was

achieving the maintenance

time. Thus, some production

parameters were adapted to

guarantee the production of

the components. These

adjusts are translated in 0.8

hours of additional

production time

Root-Cause

Statement

72

Figure 5-11 Cause analysis of the critical value of the total system cost

5.3.5.2. Lean problem-solving solutions application

The present section aims to reduce the most critical KPI pointed in the previous subsection throughout

the application of Lean problem-solving tools. Based on the root-cause information of the critical KPIs

(Setup time) a problem-solving solution was applied, and its improvement results analysed.

Firstly, a Gemba Walk was performed focused in the QC- Injection Machine [where the Setup occurs].

Then the Setup process was observed and some wastes of the time were identified. Based on that

identification, two different tools were applied, the 5S and SMED. The explanation of both tools is

presented in – subsection 5.1.

During the Setup observation, the following issues were identified:

i. The specific lubricant was not separated from the others and the employee wastes time looking

for it.

ii. The cleaning material was not close to the work area and the employee wastes time measuring

and transporting it.

iii. The new mould was far from the Machine. Consequently, the employee wasted time to look for

it into the mould warehouse.

iv. The assembling and disassembling tools were not organised and identified for the change of

the specific mould.

v. The new product folder warehouse is far from this machine and the employee wasted time.

Which parameters within the critical QC section of

the critical QC are influenced by the Total

Production Time? And how?

Space and Equipment cost due to the cost

allocation of these parameters is performed based

on the Total Production Time

Which parameters are analysed in

this section?

Labour Space Equipment

There is any unhoped value? Setup time and cost

Critical QC-Section within TPS: Total System Cost

QC that represents the highest contribution in the

QC-section above: QC -Injection Machine

Which parameter is influenced by Setup time?

Total Production Time

73

vi. The Quality control team was not expecting the approval call, and they take longer to approve

the product originating a waste of time and possibly of material since the production was already

started.

Considering these issues, a 5S tool was applied focused in the tools organisation and the preparation

of these accessories to obtain an organised and easy to access area. This tool application aims to

reduce the issues i, ii and iv listed above.

Firstly, the tools and consumables (lubricant and operating materials) were divided into the required

ones for the mould change and the ones not needed. Then, the necessary consumables were organised

on the top of the tool cart close to the Machine and organised having in consideration the sequence of

requirements. This sequence was selected based on the employee experience and the sequence of

events observed. Then, the additional equipment and materials were stored in the tool cart to promote

a clean work area.

In parallel with the previous tool, the SMED tool was also suggested to convert internal steps, into

external steps of the process. This tool’s application goal is to reduce i-v issues presented above when

combined with the previously suggested tool. The activities selected to transform into external activities,

i.e., the ones that should be performed before the mould change starts, includes the following:

1. The organisation tools, consequence of the 5S application, was performed before the end of

the previous production;

2. Prepare the new mould and storage the mould cart close to the machine;

3. Bring the overhead crane close to the injection machine;

4. Prepare the cleaning material and store it close to the tool cart;

5. Bring the new mould folder and the robot accessories to the support machine table;

6. Notify the quality control team that the setup is going to happen and they will be called in

approximately 1hr30min.

The results presented in Table 5-13 shows that the Lean tools allowed a setup reduction of 51%. After

the application of the improvement solutions, the MFCA was reapplied to check the enhancement results

based on the financial implications. Table 5-14 presents the global results of the manufacturing system

regarding the costs and the reduction after the application of the improvements.

Table 5-13 Setup time after lean tools application

Before tools

application

Expected after SMED and

5S application

Real after SMED and

5S application

Setup time 3hr 13 min 1hr 25 min 1hr 35 min

Setup reduction -56% -51%

74

Table 5-14 Final Results after Lean application tools

TPS Improvement Results After problem-solving tools

Per production KPI of TPS Units

Energy - 0,53 € - 0,02% - 6,36 Kw

System - 16,15 € - 1,72%

Product - 10,98 € Kg

Waste - 5,69 € Kg

Total Production - 16,68 € - 2% -1,59 h

Total Production time -3%

Through the analysis of the Total System Results obtained after the MFCA-Lean methodology first

application (Table 5-14) is possible to conclude that the improvements applied allowed not only, the Total

System Cost and consequently the Total Production Cost reduction in 16.15€ (-1.72%) and 16.68€ (-

2%) respectively but also, the decrease of the energy consumed. It also led to the improvement of the

OEE in 5.4%.

Thereafter a the MFCA-Lean Methodology should be re-applied to promote a continuous improvement

cycle. A revaluation of the “new” critical factors and the reapplication of the entire methodology should

be performed and in case of a lack of discrepancy between the TV and KPI a parameter's reformulation

is suggested.

5.4. Methodology application conclusions

The application of the novel MFCA-Lean methodology allows (i) the identification of the real product

manufacturing state, (ii) the cost distribution per process, (iii) the identification of improvement

opportunities (iv) the diagnosis and problem-solving analysis and solutions to overcome the production

issues and (v) the update of the production performance using the data obtained through the application

of the problem-solving solutions.

The MFCA-Lean methodology should encourage the company’s managers to re-evaluate their strategy

through the production system performance, and support their decision-making promoting a continuous

improvement cycle to tackle the market pressure.

Furthermore, during the application of this integration methodology to a case study, the critical aspects

and the improvement solution were identified, as well as applied. Then, the results were evaluated, and

its study presents a reduction in the Total Production Costs considering the type of company and

production system. The application of MFCA-Lean methodology allows the comprehension of the 3% of

reduction in the total production time led to a cost decrease of 2% in a two days production system.

Since the mould's industry is characterised by being a non-stop industry a 3% time reduction can be

translated a great impact on the company’s economy and availability.

75

6. Conclusions

The present dissertation had two main objectives. The first one, related to the validation of the

application of MFCA methodology to a production system and the assessment of its benefits when

applied as a diagnostic tool. To assess that information, during the MFCA analysis a detailed observation

was performed. Once understood the main advantages and limitations of its application concerning

production flows, aims at the development of a methodology which could integrate MFCA method with

Lean tools. To accomplish these goals, a production unit which follows a MTS strategy was used as a

first case-study, then the MFCA-Lean methodology was developed and applied to a production unit

which follows a MTO strategy. This last was used as a second case-study to validate the MFCA-Lean

methodology.

The application of the MFCA analysis through the direct application of the ISO standard 14051 [3] to a

production unit supported the company to understand the magnitude of the resources used and flows

in terms of product and waste costs. The results obtained through MFCA application reveals that the

real waste percentage was three times higher than the company expected

Hence, MFCA proved to be an appropriate tool of diagnostic in terms of monetary values. i.e, the MFCA

is an effective tool to determine the resources uses and transformed as a product or loss in terms of

monetary performance. It presents the real production cost of the production system based on an

extensive data collected and allow the analyser to directly identify some obvious inefficiencies.

Moreover, it could be a useful diagnostic tool to recognise some production inefficiencies during the

analysis and data gathering period only if it is supported by a simultaneous careful observation. As a

primary conclusion, MFCA analysis allow the accounting of all material and resources wasted based on

an extensive data and system characterization but is not prepared to take care with inefficiencies from

the manufacturing system point of view – as Lean tools.

MFCA-Lean methodology appears to overcome the MFCA limitations presented. From the observation

performed concerning MFCA and Lean tools complementarities, a literature review of both was

performed to support the MFCA and Lean tools integration possibility. Then, the methodology was

developed and successfully applied to an injection moulding production system which follows a MTO

strategy.

From the application results it was possible to conclude that the MFCA-Lean methodology allows, not

only, the understanding of the costs incurred in its production systems and its flow, but also highlights

the critical KPI through its comparison with the aimed target values. In addition, it provides specific Lean

tools to evaluate the root-cause of the problem and uses problem-solving tools to solve the existent

issues. Moreover, after the application of the proposed solutions the methodology allows the

confirmation of results in monetary units due to the performance of the improvement activities,

consequently the second aims of this dissertation is achieved.

76

As final conclusions, the MFCA method and Lean tools can be integrated. This integration based on

steps procedure allows the accomplishment of aimed results directly aligned with company’s objective

and scope. MFCA-Lean methodology is able to present the real state of the production system in

monetary units for manager’s encouragement to re-evaluate their strategy and provide tools to recognise

root-causes, support and improve employees’ activities guiding efficiently their work. This methodology

should be implemented as a continuous improvement cycle so the production process moves closer to

the ideal optimized process.

7. Future Work

In this Chapter, a few suggestions for future work in the dissertation field are presented.

Firstly, is suggested that the development of a methodology or at least a guideline to model the energy

flows independently of the material flows. The allocation of the energy under the material flow usually

neglects several types of energy waste as, vibrations or heat transfer. The efficient identification of

energy efficiencies can improve the environmental performance of a company, as well as deeper

understanding of the environmental and economic performance

Thus, is suggested the application of the MFCA-Lean methodology developed in this work in different

manufacturing systems. Since it was only applied once and to an injection moulding production process,

the scope of its applicability should be extended to support the methodology validation.

77

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=default&tx_contagged%5Buid%5D=2863&cHash=630373e06873dfab8dc1dce5fd6a2507.

80

[Accessed: 02-Jun-2017].

I

9. Annexes

Annex A - Equipment identification

The equipment used for the manufacturing process through an injection moulding system are presented

in the following table.

Table A-1 – Machines for production and its description

Machine involved in the production Description

The first picture represents an injection machine,

this machines is used by the company to create

the plastic components. Those are working

according with the schedule and the needs.

Once the injection process works with specific

temperature becomes necessary the presence of

a chiller (second picture), this machine is

responsible for cooling the water that refrigerates

the necessary components

These component is a mould one of the most

important and expensive components of the

process. It has two important functions, moulding

the melted plastic and solidifying the moulded

product. Each mould is created to produce a high

quantity of parts with a high level of quality.

The first component is a hopper dryer, these

machine is responsible for drying the material,

when the specifications require it. The second

one is a vacuum pump, in this system the vacuum

pump is responsible for the material distribution.

The plastic shredder machine is responsible for

shredding the material. This equipment is used

for recycling the material

II

The transport equipment is responsible for carrying feedstock and auxiliary materials supply, storage

and product truck loading. All this equipment are managed and used by the logistic department. By its

understanding the allocation time of the employee who managed it and the equipment cost in the correct

quantity centre was possible. Thus, its description is presented in the following table

Table A-2- Machines involved in product transportation and its description

Machine involved in product transport Description

The first picture represents a stacker forklift,

these device is used to move the material or the

product in the warehouse, and it’s mainly used to

storage the product in shelves. The second one

is an electric forklift and it’s used to move heavy

loads, it’s mainly used to transport the raw

material from the outside to the inside of the

warehouse ɪ. Both devices requires a specialized

employee to handle it.

These component is a handle forklift, is similar to

the presented before, the difference is in these

case the employee needs to be in a vertical

position, and these equipment is only used for the

transportation of the material, inside the

warehouse.

The last equipment used is the vertical palletizer,

in this case, the pallet of final product is inserted

on the base, and this base had a rotational

movement and at the same time a film roll moves

vertically. Following this movement, the pallet is

totally palletized and in the end is ready to be

storage.

III

Annex B - Company’s Teams and departments

The description of the teams and departments involved in the support to the manufacturing process are

explained in the following table. These departments operate independently, however they all have a

fundamental contribution to a proper system conduct. The clear knowledge of the teams and

departments and, therefore, a clear understanding of the process stages was essential for the definition

of the Quantity Centres (key task of the MFCA method)

Table B-9-1-Teams and departments involved in the manufacturing process

Teams/Departments Description

Management Department The management department complains the financial and

business section.

Engineering Department

The engineering department is responsible for testing, adapt and

validate the possibility of new products being produce in the

company.

Logistic Department

The logistic department is responsible for the warehouse

management and must guarantee the flow of material in the

productive process. It is also responsible, for shipping the final

product, the stock management of material and the raw material

supply, as well as the production forecast and the schedule.

Quality Department

The quality department assures the high level of the product

quality as well as the client satisfaction and the accomplishment

of the ISO norms, dimensional and apparent aspect of the product.

Maintenance Team

The maintenance team is responsible for maintain the correct

functioning of all the equipment (machines, conveyor belts…),

through the last minute problem solving.

Production

The production team is responsible for regulate the injection

machine parameters to obtain a quality product, for guarantee the

correct material flow. It also should assure the correct number of

manufactured products, according with the scheduled plan

avoiding the overproduction as well as the underproduction. It is

also responsible for a type of preventive maintenance (cleaning

the mould once a shift and the machines once a week).

IV

Annex C - Operating materials – QC and utilisation

All the operating materials presented in this Annex are used for the production system of both Parts,

and is divided per QC where they are used.

Table C-1- Operating materials

QC Operating material Frequency

Injection

Machine

Alcohol 96% Shiftly maintenance

Cleaning Cloths all the maintenances

Tribol 4020/220-2 weekly and monthly

maintenance

Petraqua and Salt monthly maintenance

Tribol 800/460; 800/220 ; 3020/100 annual maintenance

Lubricant mass annual maintenance

Packaging

Boxes 1 per 2500 parts

Plastic bags 1 per 2500 parts

Adhesive tape 1 per box

Tags 1 per box

Pallets 1 per 48 boxes of Part1

1 per 16 boxes of Part2

Foam 1 per Pallet

Final Product Palletizing film 1 portion per pallet

V

Annex D - Employees’ time distribution per QC

This annex presents the time distribution per type of employee for both case studies.

Case-study of the MTS production strategy:

Dedicated employees : Project Leader, Team Leader and employee

Table D-1 – MTS production – Employees time distribution

Component QC Project Leader

Allocation Team Leader

Allocation Employee Allocation

Product Raw Material Area 2,0% 25,0% 5,0%

Hopper Dryer 1,0%

Part 1 Injection Machine 30,0% 35,0% 5,0%

Part 1 Lid QC 15,0% 10,0%

Part 1 Lid Packaging 1,0% 35,0%

Part 2 Cup IM 30,0% 40,0% 5,0%

Part 2 Cup QC 15,0% 10,0%

Part 2 Cup Packaging 1,0% 30,0%

Part 1 Lid - Rejected 2,5%

Part 2 Cup - Rejected 2,5%

Non-dedicated employees: Raw material area Employee, Employee responsible for grinding off-

specified parts, Final Product Warehouse employee.

The non-dedicated employee time distribution is based on the time spend per each employee do

performed their tasks within theirs work time.

Table D-2 – MTS production – non-dedicated Employees time distribution

Component QC Raw material

area Employee

Employee responsible for

grinding off-specified parts

Final Product Warehouse employee

Product Raw Material Area 2,0%

Hopper Dryer

Part 1 Injection Machine

Part 1 Lid QC

Part 1 Lid Packaging 2,0%

Part 2 Cup IM

Part 2 Cup QC

Part 2 Cup Packaging 2,0%

Part 1 Lid - Rejected 5.0%

Part 2 Cup - Rejected 5.0%

Part 1 Lid- Final Product 13%

Part 2 Cup – Final Product 13%

VI

Table D-3: Production system equipment - classification and allocation results per quantity centre

Qc Equipment Type And Allocation

Raw material area Fork Lift, Electric Stacker,

Manual Stacker (Two) Non-Dedicated – 43%

Hopper Dryer Vacuum Pumps (Two), Hopper

Dryer Dedicated – 100%

Part 1 – Injection

Injection Machines, Moulds

And Accessories (Three)

Chillers

Dedicated – 100%

Non-Dedicated – 50%

Part 2 – Injection

Injection Machines, Moulds

And Accessories (Three)

Chillers

Dedicated – 100%


Part 1 – Quality Control Easy – Open Machine Dedicated – 100%

Part 2 – Quality Control Poka-Yoke Dedicated – 100%

Part 1 – Packaging Weight Scale

Manual Stacker

Dedicated – 52%


Part 2 – Packaging Weight Scale

Manual Stacker

Dedicated – 48%


Part 1– Final Product

Warehouse

Stretch Wrapper, Electric

Stacker, Manual Stacker (Two),

Electric Fork-Lift (Two)


Part 2 – Final Product

Warehouse

Stretch Wrapper, Electric

Stacker, Manual Stacker (Two),

Electric Fork-Lift (Two)


Part 1 – Waste Management

(Rejected) Shredding Machine Non-Dedicated – 22%

Part 2 – Waste Management

(Rejected Shredding Machine Non-Dedicated – 22%

VII

Annex E – Analysis to reduce the number of mouldings

rejected after stops

Considering the production conditions:

• machine 27 produces 32 lids each moulding, 40 produces 28 lids each moulding and 28

produces 15 lids each mounding.

• the daily maintenance is performed every 8 hours and the production system works 24h/day

• Is possible to reduce 15 mouldings

Is possible to save 1 231 875 products per year

Easy Open Test - Reference number kgf>5.5 and kgf<11.5

Machine 27 40 28

Moulding 5th 10th 15th 20th 5th 10th 15th 20th 5th 10th 15th 20th

Cavity Kgf

1 9.1 9.1 9.12 9.14 8.94 8.98 8.88 8.81 10.2 10.2 10.1 10.1

2 9.3 9.31 9.3 9.29 9.54 9.94 9.11 9.55 9.35 9.4 9.3 9.25

3 9.4 9.35 9.2 9.16 9.38 9.04 9.15 9.42 8.65 8.54 8.5 8.46

4 9.7 9.6 9.5 9.45 9.69 9.94 9.54 9.64 7.45 7.4 7.48 7.5

5 9.85 9.9 9.8 9.7 9.79 9.76 9.6 9.55 8.23 8.15 8.1 8.96

6 9.12 9.15 9.2 9.16 10.0 10.3 9.62 10.1 9.65 9.7 9.65 9.7

7 9.35 9.34 9.3 9.15 9.72 9.94 9.7 9.25 10.2 10.2 10.2 10.3

8 8.65 8.67 8.7 8.65 9.33 9.96 9.42 9.08 11.2 11.2 11.2 11.1

9 8.36 8.37 8.4 8.3 11.2 11.1 11.4 11.1 10.7 10.8 10.7 10.8

10 9.65 9.5 9.6 9.7 11.3 11.3 11.2 11.2 11. 11.2 11.5 11.1

11 8.45 8.6 8.6 8.7 11.3 11.3 11.4 11.3 11.1 11.1 11.1 11.1

12 7.36 7.4 7.36 7.4

10.2 10.2 10.2 10.2

13 7.41 7.6 7.34 7.15 11.3 11.4 11.3 11.2 10.5 10.7 10.6 10.5

14 7.25 7.8 7.81 7.75

10.9 10.5 10.4 10.4

15 10.6 10.5 10.4 10.3 11.2 11.2 10.7 10.5 8.28 9,00 9.01 9.5

16 10.5 10.9 10.6 10.2

17 11.2 11.1 11.1 11.1 11.3 11.2 11.2 11.2

18 10.6 10.5 10.2 10.2 11.1 11.1 11.3 11.4

19 9.58 9.6 9.4 9.4 11.3 11.3 11.2 11.2

20 11.3 11.4 11.2 11.2 10.9 11.0 10.5 11.0

21 8.45 8.6 8.5 8.5 10.7 10.9 10.1 11.2

22 8.55 8.6 8.4 8.4 11.2 11.2 11.3 11.3

23 9.58 9.6 9.5 9.51 11.2 11.3 10.9 11.0

24 7.56 7.71 7.72 7.7 10.9 11.3 11.0 11.3

25 9.47 9.52 9.6 9.5

26 9.65 9.7 9.5 9.5 9.15 9.94 9.45 9.74

27 8.93 8.94 8.8 8.81 9.93 10.4 9.47 10.0

28 10.6 10.7 10.6 10.7 9.18 9.13 9.23 9.5

VIII

29 10.2 10.3 10.2 10.3 9.5 9.7 10.0 9.98

30 11.2 11.1 11.1 11.1 9.35 9.43 9.28 9.74

31 10.4 10.3 10.4 10.3 9.35 10.6 9.45 10.0

32 11.2 11.3 11.2 11.1 9.57 9.59 9.01 9.99

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