Linköping University | Department of Management and Engineering

Master’s Thesis, 30 credits | Sustainability Engineering and Management

Spring 2020 | ISRN LIU-IEI-TEK-A--20/03881—SE

Sustainable Manufacturing: Green

Factory – A case study of a tool

manufacturing company

Rohan Surendra Jagtap (Linköping University)

Smruti Smarak Mohanty (Uppsala University)

Supervisor LiU: Simon Johnsson

Supervisor Sandvik Coromant: Peter J. Jonsson

Examiner: Bahram Moshfegh

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© Rohan Surendra Jagtap

© Smruti Smarak Mohanty

Popular Scientific Summary

Sustainable development is a hot topic trending across the world in the 21st century. It is

important to grasp the definition of ‘Sustainable Development’. One popular definition of

sustainable development is from the United National World Commission on environment and

Development is “Development that meets the needs of the present without compromising the

ability of future generations to meet their own needs”. In the 4th industrial revolution the whole

world is moving in a sustainable direction in the three domains - environmental, economic and

social. The term Sustainable Manufacturing refers to the integration of processes and systems

capable to produce high quality products and services using less and more sustainable resources

(energy and materials), being safer for employees, customers and communities surrounding,

being able to mitigate environmental and social impacts throughout its whole life cycle.

The thesis report presents a method to track energy use in the production line for a product

family i.e. turning tools. This is done by carrying out a bottom-up energy audit and creating a

map of the energy use in the entire production process by implementing the Value Stream

Mapping (VSM) method. This analysis of the energy use will help developing an energy cost

tool which quantifies the carbon footprints from the manufacturing of tools as well as from the

facility. Another outlook of the study is to develop new Energy Performance Indicators (EnPIs)

for the production and support processes. The EnPIs presents an opportunity to monitor the

energy use closely by integrating them into the energy software. Finally, another purpose of

the thesis study is to study the social sustainability dimension wherein the working environment

is analysed and discussed.

The case study result presents a huge potential in achieving higher sustainability in tool

manufacturing industries. By implementing sustainable manufacturing, the organizations could

achieve efficient productivity, such as higher quality of manufacturing, waste elimination from

the production line, re-use of the essential resources and product durability improvement

resulting in less carbon footprint. This thesis work could serve as a base for future sustainability

projects for the tool manufacturing industries.

Foreword

This Master Thesis has been written in collaboration with Linköping University. The work has

been jointly developed by Rohan Surendra Jagtap (Linköping University) and Smruti Smarak

Mohanty (Uppsala University) with the help of AB Sandvik Coromant. We both authors have

worked in most of the areas prioritized to our field of studies. In this study, I have focused on

the energy audit, energy cost tool and energy performance indicators aspect whereas Smruti

has focused on the Sustainable Value Stream Mapping and social sustainability. Both the report

shares about 80% to 90% similarity and might differ in terms of formatting and overall

structuring.

I’d like to thank Simon Johnsson my supervisor for the thesis at Linköping University who is

working as a Research Engineer in the Department of Management and Engineering (IEI)

within the Division of Energy Systems. He has helped me whenever I have faced difficulties

throughout the thesis as he has a thorough experience working with energy auditing and related

research work. While also read proofing my entire thesis report, thus making it much better in

terms of the language as well as structuring. I’d also like to thank Ines Julia Khadri, Ph.D.

student at the Department of Engineering Sciences, Industrial Engineering & Management in

Uppsala University who supervised Smruti and has indirectly also helped me with the thesis.

I would like to thank Sandvik Coromant, Gimo for their assistance in the collection of data

including all the respondents and managers that took part in our study and gave us the

opportunity to interview them with thorough input and full support. I would further like to

thank my manager at the company Peter J. Jonsson and my supervisors at company Martin

Kolseth, Lovisa Svarvare and Peter P. Andersen for their unwavering support and guidance.

I would like to appreciate all my course instructors within the Sustainability Engineering and

Management program at IEI Department at Linköping University. I am truly grateful for the

knowledge gained throughout the last two years which has complemented me in doing this

thesis work. The thesis completes my master’s studies and I have enjoyed my time at

Linköping University.

In truth, I could not have achieved my current level of success without a strong support group.

I am thankful to my parents and friends who have constantly provided me with the emotional

support and motivation especially during the Covid-19 pandemic.

Abstract

Efficient use of resources and utility is the key to reduce the price of the commodities produced

in any industry. This in turn would lead to reduced price of the commodity which is the key to

success. Sustainability involves integration of all the three dimensions: environmental,

economic and social. Sustainable manufacturing involves the use of sustainable processes and

systems to produce better sustainable products. These products will be more attractive, and the

industry will know more about the climate impact from their production.

Manufacturing companies use a considerable amount of energy in their production processes.

One important area to understand the sustainability level at these types of industries is to study

this energy use. The present work studies energy use in a large-scale tool manufacturing

company in Sweden. Value Stream Mapping method is implemented for the purpose of

mapping the energy use in the different operations. To complement this, an energy audit has

been conducted, which is a method that include a study and analysis of a facility, indicating

possible areas of improvements by reducing energy use and saving energy costs. This presents

an opportunity for the company to implement energy efficiency measures, thus generating

positive impacts through budget savings. Less energy use is also good for the environment

resulting in less greenhouse gas emissions level. This also helps in long-term strategic planning

and initiatives to assess the required needs and stabilize energy use for the long run. Social

sustainability completes the triad along with environmental and economic sustainability. In this

study, the social sustainability is reflected with the company’s relationship with its working

professionals by conducting a survey. The sustainable manufacturing potential found in the

case study indicates that significant progress can be made in the three sustainability

dimensions. Although, the scope of the thesis is limited to a tool manufacturing company,

several of the findings could be implemented in other tool companies as well as industries

belonging to other sectors.

Key words: energy audit, energy efficiency, Value Stream Mapping

Table of Contents 1. Introduction ........................................................................................................................ 1

1.1. Problematization.......................................................................................................... 2

1.2. Need of sustainable manufacturing in tool manufacturing industries ......................... 3

1.3. Objective and Research questions ............................................................................... 4

1.4. Delimitation ................................................................................................................. 5

1.5. Case Company description .......................................................................................... 5

1.5.1. About Sandvik Group .......................................................................................... 5

1.5.2. About Sandvik Coromant .................................................................................... 6

2. Theoretical framework ....................................................................................................... 7

2.1. Sustainable Manufacturing .......................................................................................... 7

2.2. Energy Auditing .......................................................................................................... 8

2.3. Energy Efficiency ...................................................................................................... 10

2.4. Value Stream Mapping.............................................................................................. 11

2.5. Cost tool in manufacturing ........................................................................................ 11

2.6. Energy Performance Indicators ................................................................................. 12

2.7. Social Sustainability .................................................................................................. 13

3. Literature Review............................................................................................................. 14

3.1. Sustainable Manufacturing ........................................................................................ 15

3.2. Energy Audit ............................................................................................................. 15

3.3. Energy Efficiency ...................................................................................................... 16

3.4. Energy Management ................................................................................................. 16

3.5. Value Stream Mapping.............................................................................................. 17

3.6. Energy Performance Indicators ................................................................................. 18

3.7. Social sustainability................................................................................................... 19

4. Methodology .................................................................................................................... 19

4.1. Literature review ....................................................................................................... 20

4.2. Research design ......................................................................................................... 20

4.3. Research approach..................................................................................................... 21

4.4. Empirical case data collection approach ................................................................... 22

4.4.1. Data collection for Bottom-up audit .................................................................. 23

4.4.2. Data collection for Sus-VSM ............................................................................. 24

4.4.3. Data collection for Energy cost tool .................................................................. 26

4.4.4. Data collection for Energy Performance Indicators........................................... 27

4.4.5. Data collection for Social sustainability ............................................................ 27

4.5. Motivation of Research Methodology....................................................................... 28

4.6. Ethical and legal consideration ................................................................................. 29

4.1. Limitations ................................................................................................................ 29

5. Result and analysis ........................................................................................................... 30

5.1. Audit .......................................................................................................................... 30

5.1.1. Survey ................................................................................................................ 30

5.1.2. Energy Analysis ................................................................................................. 31

5.1.3. Energy Efficiency Measures .............................................................................. 37

5.2. Sustainable Value Stream Mapping .......................................................................... 45

5.3. Energy Cost Tool ...................................................................................................... 48

5.4. Energy Performance Indicators (EnPIs) .................................................................... 53

5.5. Interpretation of Social Sustainability ....................................................................... 55

6. Discussion ........................................................................................................................ 59

7. Conclusion ....................................................................................................................... 62

8. Future Scope .................................................................................................................... 63

References ................................................................................................................................ 65

Appendix .................................................................................................................................. 72

Appendix 1. PI System Explorer ......................................................................................... 72

Appendix 2. Semi-structured interview template ................................................................ 73

Appendix 3. Social sustainability survey template .............................................................. 74

Appendix 4. VSM Calculation ............................................................................................. 75

List of Figures

Figure 1 The three dimensions of sustainability (Sonnemann, et al., 2015) .............................. 1

Figure 2 Different divisions of Sandvik group .......................................................................... 6

Figure 3 Classification of sustainable manufacturing, Bonvoisin et al. (2017) ......................... 8

Figure 4 Energy Audit process developed by (Rosenqvist, et al., 2012) ................................. 10

Figure 5 Concept of energy performance indicators (EnPI) in baseline period and

implemented period (ISO, 2020) ............................................................................................. 12

Figure 6 Funneling structure for literature review ................................................................... 14

Figure 7 Mixed research methods adopted for thesis study ..................................................... 21

Figure 8 Data Collection .......................................................................................................... 22

Figure 9 Iterative process for industrial audit, (Rosenqvist, et al., 2012) ................................ 23

Figure 10 System Boundaries for study ................................................................................... 29

Figure 11 Production flow for the products ............................................................................. 31

Figure 12 Active power sum L1-L3 (10m) for 2018 ............................................................... 31

Figure 13 Active power sum L1-L3 (10m) for 2019 ............................................................... 32

Figure 14 Unit Processes of GVP3, Heat Treatment and Packaging ....................................... 33

Figure 15 Sankey diagram: Product A ..................................................................................... 34

Figure 16 Sankey diagram: Product B .................................................................................... 34

Figure 17 Sankey diagram: Product C .................................................................................... 35

Figure 18 Sankey diagram: Product D .................................................................................... 35

Figure 19 Percent energy recycled from compressors ............................................................. 36

Figure 20 Percentage of energy going to the ventilation and preheating the incoming air ..... 37

Figure 21 Percentage of total instantaneous electricity of compressors .................................. 37

Figure 22 Working week total energy use in STAMA cells .................................................... 38

Figure 23 Non-working week total energy use in STAMA cells ............................................ 38

Figure 24 Organizational structure of Energy Management .................................................... 39

Figure 25 Energy Pyramid at Volvo CE (Thollander, et al., 2020) ......................................... 40

Figure 26 Procedure for implementation of energy efficiency measures (Hessian Ministry of

Economics, Transport, Urban and Regional Development, 2011) .......................................... 41

Figure 27 Pump energy use during production week in STAMA cells ................................... 42

Figure 28 Pump energy use during non-production week in STAMA cells............................ 43

Figure 29 VSM diagram for Product A ................................................................................... 46

Figure 30 VSM diagram for Product B.................................................................................... 46

Figure 31 VSM diagram for Product C.................................................................................... 47

Figure 32 VSM diagram for Product D ................................................................................... 47

Figure 33 Energy Cost Tool: Tool Sheet ................................................................................. 50

Figure 34 Energy Cost Tool: Data Sheet ................................................................................. 51

Figure 35 Output Report Sheet ................................................................................................ 52

List of Tables

Table 1 Structure of unit processes categorization (SÖDERSTRÖM, 1996) ............................ 9

Table 2 Comparison of Traditional VSM and Sus-VSM (Bown, et al., 2014) ........................ 11

Table 3 Set of templates to measure energy efficiency (Schmidt, et al., 2016) ....................... 19

Table 4 Example of losses in a compressed-air system, (Falkner & Slade, 2009) .................. 44

Table 5 Reference Chart for the Tool sheet ............................................................................. 49

Table 6 List of current EnPIs used in STAMA cells ............................................................... 53

Table 7 List of suggested new EnPIs which can be developed through available data in

STAMA cells ........................................................................................................................... 53

Table 8 List of suggested new EnPIs in STAMA cells ........................................................... 54

Table 9 List of suggested new EnPIs for support processes for the industry .......................... 55

Table 10 Results of social sustainability survey ...................................................................... 56

Table 11 Social Sustainability score matrix............................................................................. 57

Table 12 Improvement suggestions in social sustainability survey ......................................... 58

Table 13 Material removal ....................................................................................................... 75

Table 14 Operation and lead time ............................................................................................ 76

Abbreviations

SM Sustainable Manufacturing

VSM Value Stream Mapping

SUS-VSM Sustainable Value Stream Mapping

IEA International Energy Agency

PA Packaging

EnPI Energy Performance Indicator

FSSD Framework for Strategic Sustainable Development

SSD Strategic Sustainable Development

IPCC Intergovernmental Panel on Climate Change

GHG Green House Gas

KPI Key performance Indicator

EEM Energy Efficiency Measures

EE Energy Efficiency

EB Energy Baseline

EHS Environmental Health and Safety

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1. Introduction

The report by UN Intergovernmental Panel on Climate Change (IPCC) has highlighted about

the fact that the increase in global greenhouse gas emissions is rapidly altering the climate. It

states that the average global temperature will reach the threshold of 1.5 ℃ above pre-industrial

levels by 2030. Thus, causing various problems like desertification, increasing sea levels,

reducing food production etc. Energy demand reductions, decarbonization of electricity and

other fuels, electrification of energy end use etc. are some of the mitigation pathways. The

demand of low energy and land- and GHG-intensive use goods contribute towards limiting the

warming to as close to 1.5 ℃ (IPCC, 2018). The tool manufacturing industry, mining and

quarrying industries use about 49,081 GWh, while the total electricity use is 171,862 GWh

(SCB, 2018). This is about 28% of the total use, thus turning out to be a significant contribution

and a considerable share of the energy supplied worldwide.

Sweden is on track to meet its energy target to reduce the energy intensity of the economy by

at least 20% from 2008 to 2020 (International Energy Agency, 2019). The target of a reduction

of 50% by 2030 also seems to be feasible albeit further improvements are required to achieve

it (Ibid.). The energy intensity depends on the structure of the economy and the structural

changes in energy-intensive industries can potentially have a large impact on a country’s

performance (Ibid.).

Sustainable development is a hot topic trending across the world in the 21st century. One

popular definition of sustainable development is from the United National World Commission

on environment and Development is “Development that meets the needs of the present without

compromising the ability of future generations to meet their own needs” (Brundtland

Commission , 1987). This definition is based on two key concepts: “needs” which refers to the

essential needs of the world’s poor, to which overriding priority should be given; and

“limitations” which refers to the restrictions imposed by technologies and socio-economic

factors on the ability of the environment to meet the needs of present and future generations.

Figure 1 The three dimensions of sustainability (Sonnemann, et al., 2015)

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To achieve long-lasting sustainable development in an organization, there is a need to balance

environmental, economic and social sustainability factors in equal. The three dimensions of

sustainability are defined as follows.

• Environmental Sustainability:

Environmental sustainability means that we are bounded within the means of our

natural resource. To achieve true environmental sustainability, there is a need to ensure

that the use of natural resources like materials, energy fuels, land, water etc. are at a

sustainable rate or by circularity. There is a need to consider material scarcity, the

damage to environment from extraction of these materials and if the resource can be

kept within circular economy principles (Circular Ecology, 2020).

• Economic Sustainability:

Economic sustainability refers to the need for a business or country to use its resources

efficiently and responsibly in order to operate in a sustainable manner to consistently

produce an operational profit. Without the operational profits, businesses cannot sustain

its activities. Without responsible acting and efficient use of resources, a company will

not be able to sustain its operations in the long run (Ibid.). Being economically

sustainable would help to build long lasting economic models.

• Social Sustainability:

Social sustainability refers to the ability of society or any social system to persistently

achieve a good well-being. Achieving social sustainability would ensure the social

well-being of a country, an organization or a community can be maintained in the long

run (Ibid.). From a business perspective, it is about understanding the impacts of

corporations on people and society (ADEC Innovations, 2020).

The thesis primarily focuses on the environmental sustainability and economic sustainability

dimensions which is in relation to energy use tracking and how it can be made more efficient.

The tracking helps the case company to evaluate its greenhouse gas emissions and potentially

reduce it in the future through energy efficiency or other sustainability improvements. This will

in turn present an opportunity to generate operational profits in the long term while also

incorporate sustainable values, thus maintaining the interests of stakeholders and customers.

While the social sustainability dimension is briefly touched upon which reflects the well-being

of employees working in the organization. The bottom-line of the thesis is to present a case

study of a tool manufacturing company linking the three topics. The following chapters present

the problematization of thesis, objectives and research questions, delimitation set by authors

and case company background.

1.1. Problematization

Minimization of environmental impact is getting progressively significant inside

manufacturing sector as customer, suppliers and customers demand that manufacturers

minimize any negative environmental effects of their products and their respective operations

(Klassen, 2000). Managers play an imperative part in deciding the environmental effect of

assembling manufacturing operations through decisions of crude materials utilized, energy

used, toxins radiated, and wastes generated (Ibid.). In the course of recent decades, theoretical

thinking on environmental issues have gradually extended from a restricted spotlight on

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contamination control to incorporate a huge arrangement of the board choices, projects and

technologies. In this 4th industrial revolution most of the organizations want to increase the

productivity, while the environmental burdens are the major challenges for them. Increasing

rate of carbon footprint in the production facility and other supply process involved in the

complete manufacturing process is a major problem. Structural industrial changes hold quite a

lot of potential for industrial manufacturing companies in their pursuits of becoming more

sustainable. Decreased energy use and increased energy efficiency are two possible ways to

achieve increased sustainability. Sustainable manufacturing in the tool manufacturing industry

could offer a potential solution to achieve this goal.

1.2. Need of sustainable manufacturing in tool manufacturing industries

Manufacturing is experiencing a significant progress period. The presentation of applied

autonomy and robotics, 3D printing, and a changing worldwide economy have created

tremendous changes in the business, and these progressions give no indication of easing back

down (Pivot International, 2020). There is another area where manufacturing is encountering

changes, i.e. sustainability. While sustainability in manufacturing industry has been a subject

of enthusiasm for the area for a considerable length of time, as of late makers have started

looking unquestionably more truly at how to manufacture in an increasingly productive,

environmentally-friendly manner (Pivot International, 2020). Many industries consider

“sustainability” as an important aspect in their operations for increasing growth, global

competitiveness and brand awareness (Gray, 2020). Apart from that some key benefits to

sustainable manufacturing are:

• Improve operational efficiency

• Cost and waste reduction from the production process

• Long haul business feasibility and achievement

• Lower administrative consistence costs

• Improved deals and brand acknowledgment leading to more prominent access to

financing and capital

Sustainability implies working with an eye toward what's to come. Manufacturing in a

sustainable manner is a way to indicate that less environmental harm results from the

manufacturing procedure, and that is consistently something worth being thankful for (Pivot

International, 2020). Sustainability is actually very basic: If you utilize less assets today, the

industry will have more for tomorrow - regardless of whether "tomorrow" signifies quite a

while from now. It's simple for most of the manufacturing industry to think about "the

environment" as a theoretical formulation, however manufacturers know better, managing as

they do in crude materials. As assets become rare, costs go up (Ibid). Sometimes, manufacturers

need to begin utilizing substitution materials (Ibid). These issues can make logistical issues,

also an expansion in costs - and these issues can rapidly swell into significant issues for your

organization (Ibid). As the Harvard Business Review reports, organizations that focus on

sustainability early will end up in front of the pack (Nidumolu, et al., 2009). Sticking to the

strictest environmental consistence guidelines instead of the most indulgent, for instance, can

permit an organization to discharge feasible items a few item cycles in front of their rivals. This

makes an undeniable upper hand, setting the up the manufacturer to remain in front of those

competitors for quite a long time to come (Ibid).

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1.3. Objective and Research questions

The purpose of this thesis is to understand what affects the energy use most in the

manufacturing processes such as the use of compressed air and cutting fluid as well as machine

and method choices for a tool manufacturing company. This will facilitate a prioritization of

improvement areas in the future. There is also a need to study social aspects to understand the

conditions for implementing new sustainability measures within the case company. Since

sustainability stands on three different pillars, where one of them is concerned with the social

aspect. Primarily this study is focused on five main objectives i.e. to do a study of energy use

in a modern engineering industry (from a sustainability perspective); mapping energy use in

the tool manufacturing plant, to create comparable measurement figures for the various energy

sources of the machines; to develop a model for how to calculate the total energy cost for

manufacturing a certain product item in a product from a sustainability perspective; and to look

into the social sustainability point of view (Sandvik Coromant, 2019).

To address the problem, an investigation around the following research questions will be

presented in this Master thesis:

RQ 1. How can energy use be studied, mapped and its efficiency be improved in a tool

manufacturing industry?

RQ 2. How can EnPIs and energy cost tool be developed and implemented in a tool

manufacturing industry?

RQ 3. How can social sustainability be measured and improved in a tool manufacturing

company?

The research questions will be answered in the following way:

Regarding RQ 1, a bottom-up energy audit along with Sus-VSM is implemented in this study.

The first phase of the audit is survey, followed by energy analysis and energy efficiency

measures. The audit helps to study the energy use as well as leads to the suggestion of energy

efficiency measures based on current use. While Sus-VSM complements the audit to map the

energy use of different energy carriers for four prioritized products in production line. This

reflects the environmental sustainability as it would help the case company to reduce energy

use and equivalent GHG emissions in the future.

RQ 2 involves the development of new EnPIs and an energy cost tool. The proposed EnPIs for

the support and production processes helps to support energy related decision making or future

investments. The energy cost tool incorporates the production and facility in its calculation of

cost of manufacturing, energy use and GHG emissions. The two aspects eventually reflect the

economic sustainability as well as supports environmental sustainability.

With regards to RQ 3, it involves conducting a survey with ten explicit statements to study the

working environment of case company. The statements present an opportunity to investigate

and suggest improvements in their respective areas if required. This research question reflects

the social sustainability viewpoint, thus completing the triad.

As this research is focusing on the three parameters of sustainability, the research questions

were designed accordingly. The 1st research question covers the environmental perspective.

The 2nd research question supports environmental as well as economic perspectives. The 3rd

5

research question satisfies the social perspective of sustainability. The focus of the study has

been more on strategizing than on tools and techniques that facilitate implementation of energy

intensity-reducing measures.

1.4. Delimitation

Sustainable manufacturing is a broad concept which has different aspects to it like

manufacturing technologies, product lifecycles, value creation networks and global

manufacturing impacts (Bonvoisin, et al., 2017). The researchers in this study have confined

the scope only till manufacturing technologies perspective and briefly touched upon the value

creation networks. The Sus-VSM, energy audit, EnPIs fall under the category of the prior while

the social sustainability falls under the category of the latter. The delimitations were considered

based on the objectives and purpose described by the case company. Apart from this, no

specific or direct limitation was set by the researchers on the study.

1.5. Case Company description

This chapter is an empirical contextualization of a progressively tight investigation of the case

company AB Sandvik Coromant, Gimo. This sections briefs about the Sandvik Groups’

structure, glorious history (Both Sandvik Group and Sandvik Coromant), Sandvik Coromant’s

sustainable work, sustainable objectives, current and future sustainable challenges in the

manufacturing area. This also includes a basic analysis of Sandvik Coromant’s annual and

sustainable historical reports. This empirical study background study concludes with a detailed

analysis of the need of sustainable manufacturing in Sandvik Coromant and the tool

manufacturing companies.

1.5.1. About Sandvik Group

The Sandvik Group was established in 1862 by Göran Fredrik Göransson, who was first on the

planet to prevail with regards to utilizing the Bessemer strategy for steel creation on a modern

scale (Sandvik, 2020). At a beginning period, tasks concentrated on high caliber and included

worth, interests in R&D, close contact with clients, and fares. This is a methodology that has

stayed unaltered as the years progressed. As ahead of schedule as the 1860s, the item run

included drill steel for rock-penetrating (Ibid). The organization's posting on the Stockholm

Stock Exchange occurred in 1901. The manufacturing of hardened steel started in 1921 and

cemented carbide in 1942. Manufacturing of cemented carbide apparatuses started during the

1950s in Gimo, Sweden. Sandvik Group has three major business areas such as Sandvik

Machining Solutions (SMS), Sandvik Mining and Rock Technology (SMRT) and Sandvik

Materials Technology (SMT) (Ibid).

Sandvik has persuaded that sustainability is a genuine business advantage and a driver that

upgrades Sandvik's competitiveness. Most of the clients need to work with feasible providers.

Investors and Shareholders are setting sustainable guidelines to put resources into

organizations. By aligning the presentation of Sandvik's new financial objectives with its

sustainability objectives the organization needed to underline the significance of long-term

sustainable goals. Sandvik takes a comprehensive perspective on the sustainability objectives.

It thinks about its operations, supply chain and customer offerings with specific targets for each

6

of them that complement each other, and the organization continually attempting to see the full

picture and have the greatest constructive outcome.

Figure 2 Different divisions of Sandvik group

Sandvik Machining Solutions fabricates all types of tools and tooling frameworks for cutting

edge metal cutting (Sandvik, 2020). The business zone involves a few brands that offer their

own items and administrations, for example, Sandvik Coromant, Seco Tools, Dormer Pramet

and Walter (Ibid).

Sandvik Mining and Rock Technology supplies gear, devices, administration and backing for

the mining and development ventures (Sandvik, 2020). The major business areas of SMRT is

rock penetrating and cutting, crushing and screening, loading and hauling,

burrowing/tunneling, quarrying and demolition work (Ibid).

Sandvik Materials Technology creates and makes items produced using propelled hardened

steels and uncommon alloys, including cylindrical items, metal powder, strip and items for

mechanical warming (Sandvik, 2020).

1.5.2. About Sandvik Coromant

The tool manufacturing company in the present study is AB Sandvik Coromant in Gimo,

Sweden. It was established in 1942. The company is a world leader in manufacturing cemented

carbide tools like turning, milling and drilling in metallic materials (Sandvik Coromant, 2020).

It has around 1500 employee, making it a large-scale enterprise. There are various industrial

solutions in the following sectors: Aerospace, Automotive, Die & mould, Medical, Oil and gas,

Power Generation and Wind Power (Ibid).

Sustainable business is one of its primary focus. The company intends to have customers to cut

faster or use the tools longer than in the past (Sandvik, 2019). It continues to improve circularity

for customers through recycling and buy-back programs for the used tools. Another focus is on

raw materials and the packaging which will reduce CO2 emissions and increase circularity. The

commitment has led to 80% circularity through the buy-back program (Sandvik Coromant,

7

2020). It implements green factory and sustainable facilities concept where the efforts lead to

reduction in cost, energy and CO2 emissions. The emissions have been consistently monitored

over the past few years which has led to 20% reduction overall (Ibid.).

The production in Gimo is divided into two factories – manufacturing of cemented carbide

inserts and tool holders. Sandvik Coromant’s biggest customers are the metal, automotive and

aerospace industries. The plant works with cutting edge technology for the manufacturing of

products. Hence, there is a constant need to adapt to new technologies and to find more efficient

ways to produce the tools.

2. Theoretical framework This chapter presents the theoretical fundamentals covered in the thesis study. It consists of

sub-chapters for each theme relevant to the study.

2.1. Sustainable Manufacturing

Sustainable manufacturing is defined as “the integration of processes and systems capable to

produce high quality products and services using less and more sustainable resources (energy

and materials), being safer for employees, customers and communities surrounding, being able

to mitigate environmental and social impacts throughout its whole life cycle (Machado, et al.,

2019). Various definitions have been proposed to characterize the word ‘sustainability’. For

example, sustainability has been characterized by previous Prime Minister of Norway Gro

Harlem Bruntland as the casing work where in the necessities of the present age are met without

trading off the capacity of people in the future in meeting their prerequisites (Jawahir, 2008).

Some of the reasons companies are pursuing sustainability in manufacturing are: to increase

operational efficiency by reducing costs and waste; to respond to or reach new customers and

increase competitive advantage; to protect and strengthen brand and reputation and build public

trust; to build long-term business viability and success; to respond to regulatory constraints and

opportunities (EPA, 2018).

It is imperative to discuss about the overall context about Sustainable Manufacturing in general

to get a wider perspective. Bonvoisin et al. (2017) defined sustainable manufacturing solutions

in four dimensions with overlapping scopes which they identify in literature as “layers”. They

discuss the layers as follows.

8

Figure 3 Classification of sustainable manufacturing, Bonvoisin et al. (2017)

Based on the above classification of layers, it can be said the focus of this thesis falls somewhat

under the first category of “Manufacturing technologies” and also briefly under “value creation

network”. This is since the core theme in the case study is about tracking energy use in the

production line and suggestions to improve energy efficiency while also analyzing social

sustainability dimension.

2.2. Energy Auditing

Abdelaziz et al. (2011) defined energy audit as “an inspection, survey and analysis of energy

flows for energy conservation to reduce the amount of energy input into the system without

negatively affecting the output”. It is a method which helps in proposing possibilities to reduce

energy expenses and carbon footprints, thus becoming a key point in the area of energy

management. The energy audit, for an organization, helps to understand, quantify and analyze

the utilization of energy. The detection of waste takes place as well as it identifies critical points

and discovers opportunities where the energy use can be potentially reduced. Through the

means of eco-efficient and feasible practices as well as energy conservation methods, overall

energy efficiency of the organization will be more profitable. This in turn would lead to reduced

energy costs (Saidur, 2010).

According to Vogt PE et al. (2003), there are two distinct and fundamental approaches to model

a facility’s energy use: top-down and bottom-up. The requirements of bottom-up model are

metering installation and an exhaustive inventory of all facility equipment, as well as the energy

use pattern of each facility device. It is necessary to sum the energy use of all facility’s

equipment in order to determine a facility’s total energy use. While the top-down model uses

the high-level information that a facility regularly collects regarding its activities and

performance and further associating that data with the corresponding energy use. Sathaye and

Sanstad (2004) state that the fundamental difference between the two audit methods is the

perspective taken by each on consumer and firm behavior and the performance of markets for

energy efficiency.

Manufacturing technologies

• How things are manufactured

• Where the research is oriented based on processes and equipment, development of new or improved manufacturing processes, maintenance of equipment, determination of process resource use, process simulations and energy efficiency of building.

Product lifecycles

• What is to be produced

• Where the research is primarily based on product (good or service).

• The linked discipline is product design aspects like product lifecycle management, intelligent product, product sustainability assessment.

Value creation networks

• Organization context

• Where the research is oriented based on companies or manufacturing networks.

• Examples of the approaches include resource efficient supply chain planning, industrial ecology.

Global manufacturing impact

• Mechanism context

• Where the research exceeds the conventional scope of engineering.

• Examples of approaches include development of sustainability assessment methods, education and competence development, development of standards.

9

While performing an energy audit, it is important to identify unit processes. Unit processes are

used to divide the energy use of an industry into smaller parts. They are defined by the energy

service to be performed and are further divided into two categories: Production processes and

support processes (Rosenqvist, et al., 2012). The unit processes are general for all industries,

thereby provides an opportunity for comparison of a given unit process between different

industries or businesses. Sommarin et al. (2014) put forward two approaches in order to

perform a bottom-up energy audit, first one being ‘The Unit Process-approach’ and the second

being ‘The KPI-approach’. The latter approach is divided into three different levels.

• Overall figures like MWh/ton, kWh/m2, MWh/turnover etc.

• Support process-specific figures like ventilation, compressed air etc.

• Production process-specific figures such as melting, moulding etc.

The Unit Process-approach for bottom-up audit is adopted for the thesis. The first part of an

audit is setting up an energy balance diagram (Sommarin, et al., 2014). Using the unit process

categorization method, a general way of structuring data is obtained. A unit process is based

on the purpose of a given industrial process for example cooling, drying, internal transport etc.

(see Table 1) (Ibid.). There are three parts of an audit: Energy survey, Energy analysis and

Suggested measures (see Figure 4) (Rosenqvist, et al., 2012). Energy survey phase defines the

system boundary, identifies unit processes, quantifies energy supply and allocates energy to

unit processes. Energy analysis phase identifies problems within systems, idling, outdated

technologies, assesses potential for energy efficiency. Suggested measures identify possible

solutions to the problems, calculates impact of the solutions by analysis and evaluates

economic impact (Ibid.).

Table 1 Structure of unit processes categorization (SÖDERSTRÖM, 1996)

Production process

Disintegrating

Support process

Ventilation

Disjointing Space heating

Mixing Lighting

Jointing Pumping

Coating Tap water heating

Moulding Internal Transport

Heating Cooling

Melting Steam

Drying Administration

Cooling/freezing

Packing

10

Figure 4 Energy Audit process developed by (Rosenqvist, et al., 2012)

2.3. Energy Efficiency

Energy efficiency is defined as “the ratio of useful energy or energy services or other useful

physical outputs obtained from a system, conversion process, transmission or storage activity

to the input of energy” (IPCC, 2018). The 2012 Energy Efficiency Directive (2012/27/EU) set

of binding measures for the European Union to reach 2020 energy efficiency target. The target

here is defined as “20% reduction of energy use (in primary and final energy) compared to the

business-as-usual projections”. There was further increase in the target which proposed to

target 32.5% energy savings compared to a reference case, with a clause for an upwards

revision by 2023. The EED Article 8 states “large enterprises in all EU member countries must

conduct energy audits every four years, starting from December 2015”. This was established

in Sweden in 2014, through the law on Energy Auditing of Large Companies (2014:266). It

states the first audit should be done in the four-year period 2016-19. The Swedish government

introduced “Energisteget” (the Energy Step) which is a programme to support implementation

of energy efficiency measures. The large companies that have carried energy audits in

accordance with EED requirements may apply for financial support to invest in energy

efficiency measures. The total budget for the program is around SEK 125 million for the years

2018-20 (International Energy Agency, 2019).

Sorrell et al. (2000) and Palm and Thollander (2010) discussed about the barriers for the

adoption of cost-effective energy efficiency measures in industry which can be categorized into

three factors: economic, behavioral and organizational. Cagno et al. (2013) have extended this

categorization and further divided the barriers into technology-related, organizational,

information, economic, behavioral, market, competence, awareness and government/policies.

There has also been attempts to categorize the driving forces for improved energy efficiency.

Thollander and Ottosson (2008) in their research, categorized driving forces into market

related, current and potential policy instruments, and organizational and behavioral factors.

Thollander et al. (2013) categorized these driving forces into financial, informational,

organizational and external and organizational and behavioral factors. Trianni et al. (2017)

further conducted a recent study where they classified the driving forces according to the type

of action the driving force represents, for instance, regulatory, economic, informative and

vocational training.

11

2.4. Value Stream Mapping

Value Stream mapping (VSM) is an important technique used in lean manufacturing to identify

waste, by adapting, as necessary, for green and sustainable manufacturing (Faulkner &

Badurdeen, 2014). A value stream is defined as “all the actions, both value added and non-

value added, currently required to bring a product through the main flows essential to every

product: the production flow from raw material into the arms of the customer, and the design

flow from concept to launch” (Rother & Shook, 1999). Value stream mapping can be utilized

to improve any procedure where there are repeatable advances. They would then be able to

stop the line to take care of that issue and get the procedure streaming once more (Mukherjee,

2019). Table 2 presents a comparison of criteria considered in traditional VSM and Sus-VSM.

Table 2 Comparison of Traditional VSM and Sus-VSM (Bown, et al., 2014)

Type of waste/issue Traditional VSM Sus-VSM Metric type

Time waste + + Economic

Raw material waste - + Environmental

Process water waste - + Environmental

Energy waste - + Environmental

Job hazards - + Societal

Ergonomics - + Societal

Note: + sign indicates inclusion and - sign indicates exclusion.

Lean manufacturing instruments don't think about environmental and societal benefits

advantages. The prosaic value stream mapping (VSM) system looks at the financial matters of

an assembling line, a large portion of which are with respect to time (process duration, lead

time, change-out time, and so on.) (Hartini, et al., 2018). Consolidating the capacity to catch

environmental and societal execution outwardly through VSMs will build its handiness as an

apparatus that can be utilized to evaluate producing tasks from a sustainability viewpoint.

Various investigations have tended to the augmentation of VSM to fuse extra rules. Majority

share of these endeavors have concentrated on adding vitality related measurements to VSMs,

while a few different examinations allude to 'practical' VSM by remembering natural execution

for ordinary VSMs (Hartini, et al., 2018) . This examination has built up a technique for VSM

coordinated with condition metric and social measurement for ensuring sustainable

manufacture (Ibid).

Sustainable VSM recently created has a general arrangement of measurements that will have

wide application across numerous enterprises. In any case, further customization might be

expected to evaluate explicit parts of different organization (Ibid). In general, the sustainable

VSM (Sus-VSM) is normally used to evaluate economic, environmental and social

sustainability performance in manufacturing industry. In order to evaluate the, existing

measurements for sustainable manufacturing execution appraisal are analyzed to recognize

basic rules and measurements to be included for the Sus-VSM (Faulkner & Badurdeen, 2014).

2.5. Cost tool in manufacturing

According to Nord et al. (2015), in order to develop a cost model for an optimized

manufacturing company, the operation time, type of operations and carrier used should be

considered. Since it might have incredible impact on energy use in the production unit. Along

these lines, it is essential to dissect energy use in the production unit for an appropriate analysis.

12

To empower simple energy planning, leasing, and structure, it is important to have accessible

tools and techniques for energy use prediction based on the driving factors. In that manner, a

production company could budget the energy cost and plan various operations for different

products. For instance, guideline part examination is utilized to recognize significant factors of

vitality use in low energy utilization tasks. Basic direct relapses between day by day or month

to month vitality use and total energy use show great fitting outcomes solid for a further

examination (Ibid).

2.6. Energy Performance Indicators

When it comes to Energy Performance Indicators (EnPIs), it is important to know what it

implies. “Energy Performance Indicator (EnPIs) is a measure of energy intensity used to gauge

the effectiveness of your energy management efforts” (50001 Store, 2020). EnPIs are used to

understand energy performance corresponding to energy use and energy efficiency (EE) (ISO,

2020). Thus, playing a vital role in evaluating efficiency as well as effectiveness of Energy

Efficiency Measures (EEM). The implementation and monitoring of EnPIs is imperative to

support energy related decision making. EnPI and energy baseline (EB) represent two key

interlinked elements enabling measurements pertaining to EE, use and performance. EnB forms

the basis to quantify the energy performance before and after the implementation of

improvement actions. Figure 5 represents the relation between EnPI, EnB, energy target and

measurement of performance before and after implementation (Ibid.).

Figure 5 Concept of energy performance indicators (EnPI) in baseline period and implemented period (ISO, 2020)

Based on characteristics, there are four types of EnPIs according to ISO 50006 and IEA reports:

energy use, simple ratio, statistical modeling and simulation modeling used for EE

improvement (ISO, 2020; Shim & Lee, 2018). Energy use is “using the total energy use over a

period of time” for instance kWh, GJ etc. (Ibid.). Energy intensity is an example of single ratio

which is defined as “rate of energy use per unit activity data” like specific energy use (SEC),

energy use (kWh) per production (ton) (ISO, 2020; Shim & Lee, 2018; Lawrence, et al., 2019).

A statistical model could be a linear regression model or a non-linear regression model (Shim

& Lee, 2018). A simulation model can be applied over each boundary to measure the

improvements in EE as well as energy performance (Ibid.). There are three primary EnPI

boundary levels according to ISO 50006: individual, system and organizational (ISO, 2020).

Organizational level represents major interactions between departments, total energy use,

related expenses and overall performance (Schmidt, et al., 2016). System level refers to the

evaluation of process line level where a comparison can be drawn with similar processes if

possible. EnPIs on individual level are usually done for a detailed assessment of energy use

13

and related cost per manufacturing step or equipment level (Ibid.). One other categorization

according to REF divides into three explicit levels: overall figures, support process-specific

figures and production process-specific figures (Thollander, et al., 2014).

2.7. Social Sustainability

Social Sustainability is about identifying and managing business impacts considering both

positive and negative impacts on people (United Nations Global Compact, 2020). The quality

of a company’s relationship along with engagement with its stakeholders is deemed to be

critical (Ibid.). Whether directly or indirectly, companies affect what happens to its employees,

working professionals in the value chain, customers and local communities. And it is

imperative to manage these impacts proactively (Ibid.).

According to Woodcraft (2015), social sustainability is another strand of talk on sustainable

development. It has created over various years because of the predominance of ecological

concerns and technological arrangements in urban turn of events and the absence of progress

in handling social issues in urban areas, for example, disparity, displacement, livability and the

expanding requirement for reasonable housing (Ibid.). Even though the Sustainable

Communities strategy plan was presented in the UK a decade prior, the social elements of

sustainability have been to a great extent ignored in discussions, arrangement and practice

around sustainable urbanism. There is a developing enthusiasm for comprehension and

estimating the social results of recovery and urban advancement in the UK and globally. A

little, however developing, development of engineers, organizers, designers, lodging

affiliations and neighborhood specialists pushing an increasingly 'social' way to deal with

arranging, building and overseeing urban communities. This is a piece of a global enthusiasm

for social sustainability, an idea that is progressively being utilized by governments, open

offices, arrangement producers, NGOs and organizations to outline choices about urban turn

of events, recovery and lodging, as a feature of an expanding strategy talk on the supportability

and strength of urban areas (Ibid).

There is an increasing awareness among customers and stakeholders of organizations to think

about the product as well as process from a sustainable perspective right from the early stages

of manufacturing (Digalwar, et al., 2020). This global demand from the businesses and

customers initiates the need to develop methodology for sustainability assessment for

manufacturing organizations (Ibid.). Scientists argue that organizations are important actors for

creating wellbeing for the society as well as environment (Fobbe, et al., 2016). The roles of

organizations are evident when looking at the impacts of financial crisis on society. For

instance, the financial crisis of 2008 lead to austerity programs, thus affecting the social

element of communities. Thus, employment, income levels, quality of life and work

determined by the companies have an impact on social framework even beyond the economy

(Ibid.).

One of the most real and predictable drivers for industry is sustainability. This theme opens at

various issues as per the three manageability columns: condition, monetary, and social. With

respect to last one, there is a need for strategies and instruments (Papetti, et al., 2018). As the

fourth industrial revolution is progressing, so this is a second test for ventures that should be

serious decreasing their opportunity to showcase coordinating new advancements on their

creation destinations. From these points of view, the social sustainability in a workplace is

14

planned for featuring the job of the people under the Industry 4.0 worldview. Another

transdisciplinary technique to support the sustainable manufacturing is social sustainability. It

permits structuring an associated domain (IoT system) planned for estimating and advancing

social sustainability on creation destinations. The work additionally comments the connection

between social sustainability and productivity. In fact, streamlining the human works grants to

improve the nature of the working conditions while improving proficiency of the production

work. The contextual investigation was performed at an Italian sole maker. The objective of

the investigation was to improve and enhance the completing zone of the plant from a social

perspective with the point of view of computerized producing (Ibid).

3. Literature Review

This chapter intends to look further at the bodies of literature that have emerged around the key

theoretical concepts. It gives a picture of what is sustainable manufacturing and for what reason

is it significant for organizations. Likewise, brief overview of different factors and practices

utilized for this study has been introduced. To conduct the thesis successfully, it was important

to carry out a literature review of the topics mentioned in the previous chapter. The literature

review chapter consists of existing theories in the following order: sustainable manufacturing,

energy auditing, energy efficiency, Value Stream Mapping (VSM), energy cost tool, social

sustainability and energy performance indicator (EnPIs). By implementing this, the focus of

the research was specified keeping the project objectives as a reference. The following are parts

that describe the approach, the methods for data collection, the structure and the quality of the

report.

Figure 6 Funneling structure for literature review

15

3.1. Sustainable Manufacturing

The environmental concerns have become exponentially inferable from the expanding

utilization of characteristic assets and contamination. Subsequently, to address the previously

mentioned concerns it gets essential to effectively execute the sustainable manufacturing

frameworks (Zindani, et al., 2020). Successful evaluation can be made by giving the necessary

qualitative and quantitative data. Particular divisions arranged to sustainability must be worked

inside an association to advance the improvement of sustainable culture (Ibid.). Procedures

must be set up to guarantee the utilization of the methodologies and the targets for sustainable

association.

Cherrafi et al. (2016) reviewed and analyzed several literatures to integrate three management

systems in a model i.e. lean manufacturing, Six sigma and sustainability. ‘Sustainable

manufacturing’ and ‘Lean Sustainable Manufacturing’ were used as keywords in their searches

among others. They identified seven major gaps relevant in this direction: “the need to develop

an integrated metrics and measurement system to measure lean/Six Sigma and sustainability

performance; the need to develop an integrated model applicable to many industries and

functions; the need to focus more on the context of SMEs to assist them to successfully

implement lean/Six Sigma and sustainability; the need to investigate the applicability of

lean/Six Sigma and sustainability to the service industry; the need to study the human side in a

more comprehensive manner, the need to study how to extend the implementation of lean/Six

Sigma and sustainability to emerging and underdeveloped countries, and the need to cover the

pre-implementation phase” (Ibid.).

A systematic review was done by (Machado, et al., 2019) which was intended to identify how

sustainable manufacturing is contributing towards the development of Industry 4.0 agenda and

to gain a broad understanding about the links between the two. Their research suggests that

concepts of sustainable manufacturing can support the implementation of Industry 4.0 in the

following aspects: “developing sustainable business models; sustainable and circular

production systems; sustainable supply chains; sustainable product design; and policy

development to ensure the achievement of the sustainable goals in the Industry 4.0 agenda”

(Ibid.).

3.2. Energy Audit

Vogt PE et al. (2009) discussed the advantages and disadvantages of top-down and bottom-up

energy modelling techniques. The results from their research showed that the top-down model

is preferred on the “basis of cost, time to construct, model operation, model maintenance effort,

accuracy etc.” (Ibid.). They suggested that accuracy of either model is about the same (plus/

minus 5%) where the errors using the bottom-up model could appear from: “the estimates

required by numerous small loads not justifying metering; meter malfunctions; meter reading;

data collection and entry and unknown unlisted equipment additions and deletions”.

Backlund and Thollander (2015) examined the suggested and implemented energy efficiency

measures from energy audits conducted within the Swedish energy audit program. Their

research found that the largest potential for energy efficiency improvements found in audit

reports is in the support processes such as space heating and ventilation. This was applicable

to manufacturing as well as non-manufacturing firms. They also found that the implementation

rate of the suggested energy efficiency improvement measures is 53% while 47% being the

16

implementation gap (Ibid.). Andersson et al. (2016) presented a literature review of the then

present incomparability between energy audit policy programs due to differences. They

concluded that important elements such as the free-rider effect and harmonized energy end-use

data should be defined and included in the evaluation studies. They also concluded more

consistency is needed in how categorizations of EEMs are made (Ibid.).

3.3. Energy Efficiency

The Energy Policies of IEA Countries for Sweden (2019) report recommends that the

government could complement the adopted targets with a different metric to better capture

improvements in energy efficiency in the final use. It also further states the energy efficiency

targets should be aligned with Sweden’s climate targets ensuring with actions that energy

efficiency effectively helps reduce emissions. The government also should regularly assess the

contribution of taxation on energy efficiency improvements and ensure it is sufficient to

incentivize energy efficiency further in order to fulfil the energy savings requirements for 2030

(International Energy Agency, 2019).

Energy efficiency for a machine tool, is affected by intrinsic characteristics and processing

conditions (Zhou, et al., 2016). The energy efficiency for energy losses such as motor loss,

mechanical loss and hydraulic system etc. if affected by intrinsic characteristics. While from

the perspective of machining process of machine tools, reactive power losses affect energy

efficiency mainly for real output like standby energy use, air cutting energy use, reactive power

use of acceleration and deceleration etc. that are related to inertia force. (Zhou, et al., 2016)

categorized the existing energy use models into three: 1) the linear type of cutting energy use

model based on Material Remove Rate (MRR), detailed parameter of cutting energy use

correlation models and 3) process-oriented machining energy use model. They drew two major

conclusions for future study: 1) through introduction of correlation analysis of machine tools,

parts, tools and processing conditions, accuracy of current energy use models could be

improved, 2) more scientific evaluation system is required for the assessment and test of

machining tools energy efficiency.

Mert et al. (2015) presented how services can improve the energy efficiency of a machine tool

based on a case of machine tool manufacturer. They identified existing and potential services

to increase the energy efficiency of machine tools. The existing services are: Process

consulting, training, condition monitoring, retrofit; the potential services are commissioning,

training, hotline service, maintenance agreement, spare part supply, retrofit.

3.4. Energy Management

To have a successful in-house energy management practice, Johansson and Thollander (2018)

outlined ten factors. The factors included are:

• Top-management support;

• Long-term energy strategy;

• A two-step energy plan;

• An energy manager position;

• Correct energy cost allocation;

• Clear KPIs (Key Performance Indicators);

17

• Energy controllers among floor-level staff;

• Education for employees;

• Visualization and Energy competition.

They state these factors should not be a replacement for energy management standards but as

a method or tool to achieve the outlined factors for success. Their paper was carried out in

terms of Swedish context, it remains to be seen if these factors could be generalized to other

countries except Sweden. Paramonova and Thollander (2016) discussed the possibilities for

participation of industries in industrial energy-efficiency networks (IEENs) to overcome

typical industrial energy-efficiency barriers in small and medium enterprises (SMEs). They

suggest that participating in energy-efficiency networks can shift companies’ attention to

behavioral aspects as IEENs contribute towards changing attitudes and behavior by allowing

companies to learn from their own and others’ experiences. While this may be applicable to

most of the cases, but there might be instances where the companies tend to just “green wash”.

It might be so that the companies would participate in these IEENs just for the sake of it while

having no actual implementation on ground. With regards to the change of attitude and

behavior, the top-level management might turn out to be too stubborn and rigid. Thus, refusing

to accept any kind of changes in their working structure. This calls for a need where the data

could be quantified as to how many SMEs participating in the IEENs contribute to meaningful

implementation of measures. It remains to be seen if the suggested IEENs would be applicable

for large scale enterprises and not only SMEs.

3.5. Value Stream Mapping

Value stream mapping is a venture improvement device to help in envisioning the whole

production process, speaking to both material, information and other carrier stream.

Characterized value stream as assortment of all exercises value included just as non-value

added that are required to bring a productor a group of products that utilization similar assets

through the primary streams, from raw material to the end clients (Agarwal & Katiyar, 2018).

Value stream mapping empowers to more likely comprehend what these means are, the place

the worth is included, where it's not, and most critically, how to enhance the aggregate

procedure. Value stream mapping (VSM) furnishes the user with an organized representation

of the key advances and relating information expected to comprehend and wisely make

upgrades that improve the whole procedure, not only one segment to the detriment of another

(Plutora, 2020).

The thesis concentrates on VSM as it identifies which include improvement for big business

programming arrangements using a rearranged cascade system. The thesis alludes to

programming highlights as the "product" being created right now. Unlike procedure maps, or

flowcharts, that show just the means associated with the procedure, a VSM shows essentially

more data and utilizations a totally different, progressively straight configuration (Ibid.).

The way to create basic VSM is all around archived and generally utilized in industry (Rother

& Shook, 1999). Endless articles exist on the utilization of ordinary VSM the survey of which

isn't the focal point of this paper. This approach inspects endeavors to stretch out ordinary VSM

to catch supportability execution. These endeavors can be partitioned into two general classes

(Rother & Shook, 1999):

18

• Studies which are delegated environmental/energy VSM, where the centre is joining

environmental/energy appraisal in VSM.

• Concentrates that are characterized 'sustainable' VSM.

Torres and Gati (2009) broadened the EPA lean and environmental toolkit, which they call

environmental VSM (E-VSM) and approved the technique with a contextual analysis in the

Brazilian liquor and sugar manufacturing industry. The essential center is water utilization at a

definite level by partitioning water misfortunes into inactive, genuine, inherent, utilitarian, and

genuine useful misfortunes. In any case, the visual ID of water squander inside the procedure

through the progression line approach proposed isn't clear. Recognizing the absence of

accentuation on vitality utilization in VSMs, the US EPA therefore made another toolbox for

lean and energy mapping (US EPA, 2007). The utilization of visuals, for example, a vitality

dashboard to imagine if vitality objectives are met is empowered here.

Simons and Mason (2002) proposed a technique called sustainable VSM (SVSM) to upgrade

sustainability in manufacturing by breaking down GHG gas discharges. Even though it is

alluded to as a sustainable VSM, the structure doesn't legitimately consolidate cultural

measurements; they are thought to be fused in a roundabout way by excellence of following

financial or environmental benefits being joined by social benefits. Fearne and Norton (2009)

consolidated the SVSM made by Simons and Mason (2002) with sustainability metrics made

by Norton (2007) to make a reasonable worth chain map (SVCM) method by putting

accentuation on connections and data streams between nourishment retailers and nourishment

producers in the UK. Essential environmental performance indicators (EPI) set by UK

Department of Environment, Food, and Rural Affairs (DEFRA) are to be remembered for the

SVCM while other EPI's are to be chosen by the client dependent on the given procedure and

industry (Norton, 2007).

This approach considered a wide exhibit of environmental metrics, for example, vitality

utilization during the procedure, transportation, and any capacity stages just as water utilization

and material use. The SVCM technique was approved through a contextual analysis of sourcing

and pressing of cherry tomatoes over a year time span; as surveying vitality utilization was

troublesome undertaking, they replace that measurement with information from LCA directed

by Guinee (2002). Likewise, with numerous different examinations, this SVCM, as well,

doesn't consolidate any social metrics; the strategies to quantify the diverse Environmental

Performance Indicators (EPIs) or clear visualization of chosen EPI's isn't addressed.

3.6. Energy Performance Indicators

Kanchiralla et. al (2019) developed a taxonomy for the categorization of EEU and emissions

for the processes as well as identified the intensive processes through analysis of EEU and CO2

emissions in the engineering industry. They presented several potential EnPIs based on system

boundaries like organization, system, process levels for the engineering industry. The study

could not confirm if the results could be extended and generalized to engineering industries

beyond Sweden. Johnsson et al. (2019) investigated potential energy key performance

indicators (KPIs) where the scope of the research was the Swedish wood industry. They

presented currently applied energy KPIs along with their magnitudes while also proposed new

innovative energy KPIs. The authors suggest the findings of their study could be extended to

other countries apart from Sweden which possess prominent wood industry. A framework was

19

proposed by Assad et. al (2019) which predicts energy KPIs of manufacturing systems at early

design and prior to the physical product. This framework was based on implementing virtual

models to predict energy KPIs at three explicit levels: production line, individual workstations

and components as individual energy use units (ECU) (Ibid.). These energy KPIs assist the

system designers in process engineering as well as component selection by having productivity

and sustainability as a reference. A generalized calculation methodology was proposed with a

set of templates to measure energy efficiency of manufacturing activities based on three levels:

factory, process and product (Schmidt, et al., 2016). The study presented a set of templates for

five KPIs:

Table 3 Set of templates to measure energy efficiency (Schmidt, et al., 2016)

Type 1 Energy […] per […]

Type 2 Site energy […]

Type 3 On-site energy efficiency or efficiency

increase

Type 4 Improvement or savings of energy […]

Type 5 Total value of energy […]

Andersson and Thollander (2019) discussed about the barriers and drivers in the utilization on

energy KPIs. The authors ranked the drivers for the development of energy KPIs in their study.

The top 4 ranked drivers are: monitoring energy end-use, energy targets, evaluation of energy

efficiency measures, identification of energy efficiency potential. While they ranked the

barriers of energy KPIs in the following manner: lack of resources, not prioritized, lack of

skills, lack of information, lack of relevant KPIs and too much available data (Ibid.). Their

study was applied in the context of Swedish pulp and paper industry.

3.7. Social sustainability

Schönborn et al. (2018) examined a correlation between corporate social sustainability (CSR)

culture and the financial success of a company. They conducted this study by examining

through a multiple regression analysis of two contrasting European polls, examining items

indicating CSR culture and financial outcomes. Their research showed that there are four

specific success-related social sustainability dimensions of corporate culture which are

predictors of a company being classified as financially successful. These four are:

“Sustainability strategy and leadership; Mission, communication and learning; Social care and

work life; and Loyalty and identification” (Ibid.).

4. Methodology This chapter gives an overview of the methodology adopted for the thesis study. It describes

the research design chosen, research approach undertaken, case data collection approach,

motivation of research methodology and states limitations of the study. The authors tried to

find journal articles which established a relationship between an audit process, VSM and social

sustainability aspect. After analyzing the studied journal articles, the gap in the literature was

identified. To be specific, there was no research found regarding the bottom-up energy audit

approach with Sus-Value Stream Mapping (Sus-VSM) and working environment study of

organization. The ethical and legal considerations are also covered in this chapter.

20

4.1. Literature review

The topic names were used as the keywords for searching the literature. Several academic

journals which were relevant to the topics were searched and analyzed. Science Direct was

primarily used as the database to search the journal articles, while a few articles were searched

in Springer database and Taylor & Francis database. The relevant materials included: official

websites, books, journal articles, reports and conference proceedings. Funneling process was

used which refers to the process of narrowing possible ideas into specific research question or

purpose (Shields , 2014). This helps to narrow down a big picture into manageable research

project (see Figure 6). By implementing this, the focus of the research was specified keeping

the project objectives as a reference.

The Figure 6 represents the theoretical research methodology, where the design of the chapters

with the overall study methodology can be linked to a funnel method at the first stage of the

study. The theoretical research methodology begins with the introduction which includes the

scope of this study and the structure. After that many literatures have been identified and

categorized then the three-research questions were developed.

4.2. Research design

This is a general case study approach. A case study is a research approach that is utilized to

create an inside and out, multi-faceted comprehension of an intricate issue in its genuine setting

(Crowe, et al., 2011).

This research will be done as a single case study. That is, after intensive thought the researchers

locate that a case study would be the most fit research structure. To respond to the research

questions while the researchers can focus and increase profound information inside one explicit

association. In this way a case study is generally appropriate for this study. The outcome of

this study may be not only useful for the tool manufacturing industry but also for the other

manufacturing sector.

As this study was covering a wide area, so there was a continuous data collection process was

going on through meetings, repetitive discussion with the operators and the responsible

managers. The design of the chapters with the overall study methodology can be linked to a

funnel method at the first stage of the study. The following are parts that describe the approach,

the methods for data collection, the structure and the quality of the report. The data collection

phase is concluded for both, energy audit, social sustainability and VSM.

21

4.3. Research approach

Figure 7 Mixed research methods adopted for thesis study

The methodology utilized in this study is abductive, which is more towards deductive

methodology than inductive as this study has significantly been impacted by past investigation

and research. The Figure 7 represents the methodological approach used in this thesis. There

are two sorts of strategies accessible i.e. Quantitative methods relies upon estimations, science,

measurements, reviews or numerical investigation of information while qualitative method

expects to accumulate an inside and out comprehension of an in depth understanding (Bell, et

al., 2019). The quantitative method includes the historical data review and the energy

measurements conducted through the energy audit. The qualitative method includes the social

sustainability survey conducted and the semi-structured interviews in order to get the required

information.

Since the investigation goes to and fro as far as hypothesis and empirical findings the most

proper methodology will comprise of a blend of both deductive and inductive methodologies

(Ibid.). The underlying thought of the applied research approach was the purported deductive

methodology which is a connection among hypothesis and research. Where hypothesis is

building speculation, which is basically examined experimentally (Ibid.).

22

4.4. Empirical case data collection approach

Figure 8 Data Collection

Figure 8 represents the data collection approach for study. Mainly this study consists of two

major data collection approach i.e. primary and secondary data collection. The primary data

collection consists mainly in two ways. The semi-structured interviews and the survey helped

to get the technical information about the production process. The 2nd part of the primary data

collection is energy audit which includes the electricity, compressed air and cutting fluid

measurement. Finally, to assess the working environment of the case company respectively to

know about the working environment a survey has been conducted with a 54-sample size which

was the target audience and received a response from 33 respondents.

The secondary data collection approach is based on the theoretical perspective, which includes

literature review and the historical data. The literature review helped to get some theoretical

input for the study whereas the previous historical data help to get some energy invoices of the

case company. To gather the technical data for the study semi-structured interviews were

directed.

There were two methods used overall – Bottom-up audit, Sus-VSM. Furthermore, energy cost

tool was developed through the data collected in the audit process. The bottom-up audit was

both quantitative and qualitative whereas the Sus-VSM was only quantitative used for mapping

the products. It can be said that the bottom-up audit complements the implementation of Sus-

VSM method. Ultimately, energy efficiency measures were proposed based on the energy audit

which would help the company to plan and invest in the future.

The data collection for the Bottom-up audit and Sus-VSM was interlinked and thus carried out

simultaneously. The data collection has been through conducting meetings and semi-structured

interviews with the employees of at the case company. The term 'semi- structured interview'

that covers a wide scope in qualitative research (Bell, et al., 2019). Semi-structured interview

is best utilized whenever researchers won't get more than one opportunity to talk with

researchers and when researchers will send a few questioners out into the field to gather

information. The Semi-structured interview guide gives an away from of guidelines for

questioners and can give solid, practically identical subjective information (Robert wood

23

Johnson Foundation, 2008). Semi-structured interview is frequently gone before by perception,

casual and unstructured talking to permit the researchers to build up a sharp comprehension of

the subject of intrigue important for creating significant and significant semi-organized

inquiries. The incorporation of close-ended questions and preparing of questioners to follow

significant subjects that may wander from the interview guide does, nonetheless, despite

everything give the chance to distinguishing better approaches for seeing and understanding

the current point (Ibid).

The qualitative semi-structured interviews were conducted based on a pre-decided set of

questions. A sample size of five employees were considered who closely worked with the

departments within the system boundary. Due to the information being sensitive, it is not

possible to enlist a detailed summary of the questions regarding the energy carriers and as to

why exactly they are being used. The details of the interview are presented in the form of a

table which states what energy carrier is being used in which operations (see Appendix 2. Semi-

structured interview template).

4.4.1. Data collection for Bottom-up audit

The energy audit is combined with iterative method as described in (Rosenqvist, et al., 2012).

This is since the actual workflow is not linear but an iterative process. This iteration is stopped

when there is enough data to suggest efficiency measures. This is described as follows in Figure

9.

Figure 9 Iterative process for industrial audit, (Rosenqvist, et al., 2012)

The focus of this thesis was for four products which are turning tools. Thus, the data collection

phase was primarily focused on four products. The operations and material lists were obtained

for all the products. This involved information about the machining codes of operation, name

of operation, time/piece, setup time etc.

The first phase of the audit was Survey. The Survey phase is applicable to both bottom-up

energy audit as well as Sus-VSM method. Before the start of execution, the system boundaries

and scope were defined (Bell, et al., 2019). The active power invoices for the Industrial Area

1 was collected for the year 2018 and 2019, thereby providing an overall picture of the

company. But as mentioned previously, the study was carried out in GVP3 (part of the main

workshop at the case company) inside the workshop ‘V66’, Heat Treatment and Packaging

department. The different machining operations in the manufacturing facility were identified

in the facility. The STAMA (automatic machine based in the V66 workshop in the case

company) machines were fitted with sensors and the data was collected in a separate software

known as PI System Explorer. The energy loggers were inserted for a week inside the SCHMID

(semi-automatic machine based in the V66 workshop in the case company) machine and Heat

24

Treatment. Unfortunately, due to limitations, it was not possible to get the energy use data for

the Packaging. The time interval of one minute was set to get the total energy use in kWh. This

data was collected in a software which was provided in the form of Excel document by the

Electric Department at case company.

The operations ‘Machining 1’ and ‘Machining 2’ are carried out in GVP3 while Heat Treatment

and Packaging have a separate department. The data collection started with the ‘Machining 2’

operation as it is carried out in STAMA machine cells (GVP3) which is connected to various

types of sensors. The data collected from the sensors was readily available in a software called

“PI System Explorer” (see Appendix 1. PI System Explorer). The sensors connected measures

information like energy use, supply and return temperature of cutting fluid, volume of fluid,

volume of compressed air supplied, power use etc.

The collection continued for the ‘Machining 1’ operation next, which takes place in SCHMID

machine cell in GVP3. There are total two SCHMID machines in GVP3. The energy logger

was inserted in SCHMID machine 2 cell for a duration of one week. This monitored the energy

use for the whole week where different work order was processed and manufactured. Further,

the data was collected for the Heat Treatment operations. The energy logger was inserted in

the switch cabinet specific to the operation. This was for one week each for the two operations.

The energy loggers were not kept for Packing operation. Hence, the values for electricity use

for this operation is not available for the different products.

The operation ‘M + ASY’ which refers to Measuring and Inspection, is done manually by the

operators. The case company takes a few samples from the work order and check if the

tolerances are within limits and if the dimensions are appropriate. Hence, this operation does

not use any energy. The invoice of the compressed air was also collected. This comprised of

energy data regarding heating systems, recycling to ventilation, heat that cannot be recycled

and total instantaneous electricity. This monthly invoice was for the year 2017 and 2018. There

are six and four compressors operating at the same time which are installed close to V66

facility. They supply the compressed air to the all the facilities in Industrial Area 1.

The second phase consists of Analysis. The data gathered from the first phase is analyzed

further after the removal of loggers. The data for energy use per piece was also collected for

the different carriers like electricity, cutting fluid and compressed air. Surveying phase helped

in the helped in the identification of unit processes, although the quantification of energy use

specific to its processes was not possible due to them being highly integrated and automated in

the machine cell. The energy use for different work orders is compared as well as for the non-

working week with the working week of production. Finally, energy efficiency measures were

proposed which would help the MNCs to plan, take decisions for investments in the future.

4.4.2. Data collection for Sus-VSM

The data collection for VSM was primarily conducted in the form of semi structured interviews

with the case company engineers working in different departments (see Appendix 2. Semi-

structured interview template). Engineers within the Departments of CAD/CAM, Heat

Treatment and Packaging were interviewed in order to get the required information. The

25

interviews were conducted for all the four products which would eventually lead to the creation

of four VSM diagrams.

The meetings helped to know more about the production processes and related operations for

the products within the selected facility. The different environmental metrics were identified

which consisted of time, raw material usage and process energy use. The information regarding

energy carriers (compressed air, electricity, cooling, cutting fluid) are presented inside the

boxes of diagram. Parameters like lead time, uptime and downtime for the operations were

identified by analyzing the historical and current data from the PI System Explorer. The plant

performance software helped to find the exact operation time in order to complete the Sus-

VSM diagram. By analyzing the previous historical data, the material usages were calculated

in the diagram. Thus, there will be four Sus-VSM diagrams drawn for the four products with

their respective detail, thereby tracking the energy use of the production line.

Regarding the metrics of the VSMs, the data collection for Value Stream Mapping also

included the data previously collected from the Energy Audit. This was used for the energy use

metric in the VSM diagram. The data regarding the raw material usage was collected from the

CAM Engineers, Engineers working within Heat Treatment and Packaging departments. The

same is applicable to the time metric considered in the VSM diagram.

The following metrics are considered for the formation of Sus-VSM diagrams:

1. Raw material usage metric

The energy use and raw material usage to produce the product account for almost 50% of

costs in manufacturing (Sygulla, et al., 2011). The largest material waste in manufacturing

relates to quantities lost through removal processes leading to increased scrap material

(Faulkner & Badurdeen, 2014). Thus, capturing effectiveness of raw material usage in Sus-

VSM is important and is included in the Sus-VSM for this purpose.

The manufacturing steps are broken down to two types – additive and subtractive (Sygulla,

et al., 2011). Subtractive manufacturing includes operations that involve material removal

such as machining of a gear or in this case, material removal from milling etc. (Ibid). It is

quite useful to know the material added and removed at each operation because the initial

and final raw material usage may not give the intermediate details. Thus, it becomes

imperative to include the raw material usage metric which helped to track the mass added

or removed at each operation.

The metric is represented on the Sus-VSM using two lines. One line is for the initial raw

material mass and the final for the finished product. This is used as a reference for the other

line. The processes which involve removal of materials and addition of material was placed

below or above the reference line in the form of boxes. For a process which does not add

or remove material from the product is kept as a line without any boxes.

2. Energy use metric

The energy use has a direct relationship to environmental sustainability due to the use of

non-renewable sources of energy and the corresponding GHG emissions (Ibid.). Therefore,

the energy use metric becomes important in the Sus-VSM diagram. The energy use metric

identifies the amount of energy used by each operation in the production line. The

identification of energy use at each operation will enable which operation possesses high

26

energy demand and indicating the need for further analysis and improvements. The values

are retrieved from the energy audit conducted for the studied facilities. These are

represented in the form of square boxes which are further divided into the energy use for

each carrier. There is a box at the bottom right corner which shows the total energy use as

well as the batch size considered for the complete order.

3. Time metric

The time metric is an important metric considered for the Sus-VSM which will indicate the

value-added time and the lead time for the entire production. The level above line indicates

the lead time between the two operations while the level below the line indicates the time

required for manufacturing for the respective operation. The lead time calculated from this

metric will give rise to further investigation and area of improvements for increased

productivity thereby reducing the overall time required for the whole production. Hence,

the time metric is included in the Sus-VSM diagram.

4.4.3. Data collection for Energy cost tool

The energy cost tool is developed by identifying important parameters for the selected

products. The different carriers like cutting fluid (pump energy), electricity and compressed air

are considered. The data for the parameters is collected from the energy audit process and is

served as the basis for the development of tool. The SEK per unit kWh price is identified for

the company depending upon the energy supply. The energy cost tool is developed in Excel

software. The tool is split into three sheets – tool, data and report. The tool sheet presents the

actual tool where the calculations are integrated. The tool sheet is explicitly divided into two

categories, Production and Facility. The Production category caters to the calculation from the

manufacturing operations like Machining 1, Machining 2, Heat Treatment and Packaging. The

first table in the tool sheet requires the user to input the values from the data sheet. To simplify,

tutorial boxes are used as a reference for the user such that the user knows where to input

values. The second table considers the calculation of energy use per piece, total energy use for

the batch size, total cost for production and the equivalent total GHG emissions released. The

third table in the tool considers the energy use per machine where the total number of machines

is identified in the studied facility. This calculates the energy use per machine. The Facility

category considers the total district heat used in the facility department. As the cost per unit for

district heat is identified, the total energy cost for facility is calculated and the equivalent GHG

emissions. The actual cost of supply for electricity and district heat has been omitted from the

tool due to confidentiality and are represented by different values. The energy use for support

processes represent different values than reality due to confidentiality. There have been some

important assumptions made in the energy cost tool. The assumptions are mentioned as

follows:

• The GHG emission factor for electricity has been assumed to be 0,13 kg CO2eq/kWh

(Johnsson, et al., 2019).

• The energy use per machine has been assumed to be equal for all the machines in order

to simplify and approximate. This provides a rough estimation, giving an overview of

the energy use per machine in Industrial area 1.

• GHG emission factor for district heating has been assumed to be 0,0556 kg CO2eq/kWh

(Johnsson, et al., 2019).

27

• Energy per piece values in data sheet has been calculated as average of all the sampled

values from PI System Explorer for that respective energy carrier and product.

• For the Machining 1 operation, Product E is assumed to be equivalent for all the

selected products. Hence, the electricity required per piece is the same for all.

• For Packaging operation, the compressed air is taken directly proportional to the

number of connection pipes and its equivalent area with reference of Machining 2

operation.

A ‘Reference Chart’ is outlined in the tool sheet. This enables the user of the tool to understand

which energy carrier is being used in which manufacturing operation. If an energy carrier is

being used, it is denoted by a ‘✔’ symbol and if not then ‘X’ symbol. The data sheet includes

all the energy use data regarding the different operations for the respective products. The data

is formulated in terms of tables for the energy carriers. Finally, the output sheet is presented at

the end, which fetches the data from the values inserted in the tool sheet. This sheet consists of

a brief summary of the total energy use and costs (electricity and district heat) and total GHG

emissions. It also contains five pie diagrams which give a distribution of energy use and GHG

emissions released in different areas. The five pie diagrams mentioned are – total energy use,

production energy use distribution, support processes energy use distribution, total GHG

emissions and GHG emissions between production (electricity) and facility (district heat).

4.4.4. Data collection for Energy Performance Indicators

The methodology for EnPIs was carried out in accordance to the method implemented by

(Kanchiralla, et al., 2020). The theory mentioned in the paper served as a reference to suggest

new EnPIs. The paper was thoroughly studied and analyzed, thus the EnPIs are inspired from

it. There were four explicit EnPIs tables derived. First table shows the list of EnPIs used in

STAMA cells. This table showcases the current EnPIs which are used in the PI System

Explorer software serving the purpose of monitoring and collecting energy related data. These

EnPIs were retrieved from the software. The EnPIs enlisted by Kanchiralla (2020) was used

for Table 7, Table 8 and Table 9. Table 7 shows the list of new EnPIs which can be derived

through available data from the software or through production data invoices. Table 8 shows

the list of suggestions of new EnPIs which require additional data currently unavailable in the

software and may/may not be available in the production data invoices. The information

relevant to these EnPIs are also presented below the table which could be useful if it were to

be implemented in the future. Table 9 shows the new EnPIs corresponding to the support

processes. As of now, almost all the EnPIs currently available in the software correspond to

the different machines used in the production line. The integration of this would require

additional sensors for the prioritized support process like pumps, compressors, ventilation,

lighting etc.

4.4.5. Data collection for Social sustainability

In this research work, the social sustainability assessment was conducted through a survey

questionnaire. That surveys contain a total of 10 questions and most of the questions are

developed by considering the sustainability goals. The social sustainability was assessed

through this survey. This survey was consisting of a questionnaire (Both in English and

Swedish) which was sent out to the working professionals at the case company. It was

28

important to keep the list of questions simple so that most of the participants could respond

without any difficulty. Simple random sampling method has been followed. The simple random

sample is the most essential type of likelihood sample. With random sampling, every unit of

the population has an equivalent likelihood of consideration in the sample (Bell, et al., 2019).

As this survey was conducted in the case company by considering the full-time employees of

four departments, which was around 54 (sample size) and the total population was 450 at the

case company (full time employees). This study was focused on the production process, so the

target group were chosen those were directly involved with the production process. There were

several departments, out of them four departs were chosen, so the sample size was 54. This

survey was not dependent on the employee’s availability (Ibid.). There was a scoring matrix

table formed based on the answers received from the survey. Ratings were provided to the

answer of statements. This was given as follows.

• “I agree” statement was given a rating of 4.

• “I somewhat agree” was given a rating of 3.

• “I somewhat disagree” was given a rating of 2.

• “I disagree” was given a rating of 1.

The number of responses received for the statement was multiplied by the rating provided as

mentioned above. For example, in statement one which says “Sandvik Coromant in Gimo is

actively working with sustainability” recorded 23 responses under “I agree”, thus it was

multiplied by 4 in the scoring matrix which gave 92 as a result. This was done in a similar way

for all the statements. At the end, an average score for that statement was calculated which was

out of “4”. Higher score meant that there is a higher satisfaction with that statement whereas a

lower score meant a lower satisfaction. A score of “3,6” and above was termed as good where

there is no need of much improvements while a score below “3,6” and below was deemed as

areas which could be improved further. During this social sustainability survey all ethical

parameters have been followed. Then the results of the survey were interpreted to give an

overview of social sustainability within the case company.

4.5. Motivation of Research Methodology

The bottom-up energy audit method is necessary in order to track the energy use of the products

requires measurement and analysis from the machine level. This gives rise to a bigger complex

system, thus making the original system a sub-system of the new emerging system. The audit

helps in studying and analysis of the energy use within the system boundary. The bottom-up

approach focuses on individual technologies for industrial processes (Sathaye & Sanstad, 2004)

which was the requirement in this study. While the Unit-Process-approach was used in this

audit as it is a general way for structuring the data for various processes (Thollander, et al.,

2014). This method of categorization helps to compare and generalize across all the companies

regarding process-specific comparisons between industrial companies with regards to for

example energy efficiency (Ibid.). The result from the audit will be energy efficiency measures

which would help the company for future investments. The Sus-Value Stream Mapping method

helps to visualize with clarity the present state of performance of a production line (Faulkner

& Badurdeen, 2014). The identification of relevant metrics and their visual representation helps

to develop comprehensive sustainable VSM (Sus-VSM). The energy cost tool was developed

through the data and analysis from the energy audit which will help the company in the future

29

to approximate costs generating from the different carriers of energy. The EnPIs are developed

so that the case company could monitor its energy end use more closely in the future and also

potentially evaluate its carbon footprints in real time. The survey related to working

environment was conducted among the employees (total 54 employees), which will be helpful

to identify the major factors need to consider while implementing social sustainability in a tool

manufacturing industry.

4.6. Ethical and legal consideration

Two main ethical issues were encountered during this research at the case company, data

management and invasion of privacy issues. The first issue concerned the data management

i.e. the routine collection and storing of digital data and the practices of data sharing raise new

concerns about confidentiality and related other ethical issues. Few questions raised about the

extent to which information can legitimately be used for research purposes that may be

different from the original reason for collecting the data. This issue focuses on who owns the

data and under what circumstances researchers are entitled to use it (Bell, et al., 2019).

The second ethical issue arise i.e. invasion of privacy is all about guaranteeing obscurity and

secrecy according to the chronicle of data and the upkeep of records identifies with all

techniques for business look into (Ibid.). Prior to doing the data collection and the

measurements, all the work was asked to the responsible employee for their consent. They were

also introduced to the motivation and purpose of such data collection. After that, most of the

data validated by the responsible employees at the case company and corrected some uncleared

information related to a few specific operations.

4.1. Limitations

Figure 10 System Boundaries for study

There have been several limitations considered for the thesis. The studied facility is inside the

V66 workshop, specifically GVP3 instead of the whole factory along with Heat treatment and

Packaging departments. This area comes under “Industrial Area 1” of the plant and falls under

30

site Gimo. It was not possible insert loggers inside the switchgear of the plant. This in turn,

changed the focus of the thesis where the data was readily available. The data collection has

been affected due to the ongoing Covid-19 situation, thereby affecting the results directly or

indirectly. The machines from which data was collected were in the Machining 1 and

Machining 2 operations inside GVP3. The STAMA machine (in Machining 2 operation) is

fitted with various type of sensors which measured parameters like machine electricity use

(kWh), power used (W), air use, supply and return of cutting fluid and compressed air etc.

While the parameters in SCHMID machine (in Machining 1 operation) and Heat Treatment

had to be measured manually with the help of energy loggers. As the company has thousands

of products, it was important to restrict to few products and study in detail about them regarding

its energy use. This data is collected on product level. Hence why there were only four products

selected for the study based on the company’s prioritization. Furthermore, the measurements

did not coincide with the manufacturing dates of prioritized products, hence similar product

was identified which would approximately have the same value as them. There was no

possibility to measure the electricity for the compressors and its related efficiency.

In the Value Stream Mapping (VSM) diagrams, the metrics have been identified based on the

environmental perspective of sustainability. The receiving and shipping have been excluded,

thus the focus solely being on manufacturing of the product inside the factory. This was

calculated only for ‘Machining 2’ operation due to the availability of sensors. Parameter like

pump energy requirements is also restricted to ‘Machining 2’ operation. For the rest of the

operations, only electricity energy use has been calculated. The risks associated with the

operations have been excluded as well as they were beyond the scope of this thesis. The Sus-

VSM diagrams considers only a few carriers like electricity, cutting fluid (pump energy),

compressed air and cooling water. The metrics have been limited to time, raw material usage

and energy use. The data collection about the operations overall has been restricted to only

those which were used to manufacture the prioritized products. The sample size for the social

sustainability survey was 54, which was relatively small compared to case company’s total

employees.

5. Result and analysis This chapter represents the empirical results of the research work. It also describes the

analyzation of the collected data with and concludes with some short outcomes. This chapter

represents the detailed description of the study and the results for the thesis.

5.1. Audit

The bottom-up energy audit has three phases – Survey, Energy Analysis and Energy efficiency

measures. These are described as follows.

5.1.1. Survey

There was no specific energy invoice for GVP3 or the other departments. Hence, there was a

necessity to carry out the bottom-up approach from the machine level to fulfil the purpose of

the thesis. The operations for the products are the same and involve 5 operation sequence. The

raw material in the process flow are in the form of raw blanks which undergo further machining

operations (see Figure 11). The different machining operations are listed as follows.

31

1. Machining 1

2. Machining 2

3. Heat Treatment

4. Assembly and Inspection

5. Packaging

Figure 11 Production flow for the products

5.1.2. Energy Analysis

The invoices of the active power sum L1-L3 with a duration of 10 minute was collected for the

year 2018 and 2019. This is applicable for the whole of the Industrial Area 1. As seen from the

diagrams, the curve dips during the month of July due to the low production. Apart from this,

there is regular production in the other months excluding some minor dips due to problems like

maintenance or other issues.

Figure 12 Active power sum L1-L3 (10m) for 2018

32

Figure 13 Active power sum L1-L3 (10m) for 2019

The Unit Processes was identified which comprises of GVP3, Heat Treatment and Packaging

department. The diagram consists of two categories of processes: Production and Support. The

Production processes are needed to manufacture the products. The Support processes are

needed to support the production processes but not needed for production (Rosenqvist, et al.,

2012). The unit processes have been identified which come under the system boundary. Due

to the production processes being highly automated inside the machine cells, it was not possible

to quantify the electricity use for each process.

33

Figure 14 Unit Processes of GVP3, Heat Treatment and Packaging

Sankey Diagrams

In this section, the Sankey diagrams are presented for the four products. In these diagrams, the

energy flow of the operation is directly proportional to the width of the arrows. The diagrams

consider three energy carriers – electricity, cutting fluid (pumping energy) and compressed air.

The values for all the energy carriers are represented in terms of energy use per piece. The

values which were unavailable are termed as “missing”, while the value “0” indicates not in

use. The dotted lines are linked with the missing values. The width of the lines is according to

the values, higher the value higher the width and vice versa. The width of the missing values

also changes based on assumptions. It is assumed Heat treatment operation will use more

electricity than Packaging operation. The width of compressed air for Machining 1, Heat

treatment and Packaging is kept the same. The dash dot line for the compressed air in packaging

assumes the energy use proportional to area and number of connecting pipes with reference to

Machining 2 operation. As they are based on rough assumption, it has been indicated by a dash

dot line. The width of the lines is according to the values, higher the value higher the width and

vice versa. The width of the missing values also changes based on assumptions. It is assumed

Heat treatment operation will use more electricity than Packaging operation.

34

Figure 15 Sankey diagram: Product A

Figure 16 Sankey diagram: Product B

35

Figure 17 Sankey diagram: Product C

Figure 18 Sankey diagram: Product D

36

Compressor system

Four and six compressors are operating at the same time which are installed nearby to V66

workshop. This distributes compressed air to all facilities not just V66. One compressor would

probably be more than enough for GVP3 while the six and four compressors feed the whole

Industrial Area 1. The type of compressor installed are Rotary screw type (oil) with on-off load

feature combined. The set pressure inside the compressors is 9,25 bars. The compressors

possess a heat recovery system. The compressed air system is central, and the machines are

supplied with compressed air through different sub-distribution systems. The invoices of the

compressors were studied and analyzed. It was collected for the year 2017 (January data

missing) and 2018. The main parameters considered in the invoices were the ‘total energy

recycled from compressors’, ‘recycled energy going to ventilation and preheating the incoming

air’ and ‘total instantaneous electricity’ in MWh. The exact values are not represented due to

confidentiality but instead are represented by the percentage. The percentage recycling has

been calculated by dividing monthly recycled energy (kWh) by the total energy recycled (kWh)

in that year. This shows which months have lower recycling and which months have higher

recycling. The percentage for the recycled energy for ventilation and total instantaneous

electricity has been calculated by similar method and the variation is fairly even during the

entire year. The total instantaneous electricity was increased by 7,81% in 2018 as compared to

2017. The following graphs illustrate the three parameters.

Figure 19 Percent energy recycled from compressors

37

Figure 20 Percentage of energy going to the ventilation and preheating the incoming air

Figure 21 Percentage of total instantaneous electricity of compressors

5.1.3. Energy Efficiency Measures

This section presents potential energy efficiency measures based on the audit analysis. It is

difficult to quantify the energy efficiency percentage increase. The measures are merely stated

qualitatively and thus could act as guidelines for future investment related to energy efficiency.

The measures are mentioned as follows.

1. In-house energy management

For the purpose of comparison, the energy use of a working week with a non-working week

was analyzed and compared. The time period was kept the same which would give accurate

comparative results regarding the total energy use in the Machining 2 operation. The machines

used in this operation is known as ‘STAMA’. This total energy use is inclusive of machine

energy, compressed air energy and pumping energy use. The data was collected through the PI

38

System Explorer software. The results from this requires further analysis and investigation in

the future as to where exactly the energy is being consumed, these are stated as follows. The

period was kept the same. The production week data is from 10th February to 15th February

2020. The non-production week data is from 17th February to 21st February.

Figure 22 Working week total energy use in STAMA cells

Figure 23 Non-working week total energy use in STAMA cells

As seen from the graph, the non-working week where the production is closed down still

consumes a substantial amount of energy when compared to working week of production. The

non-working week is still consuming approximately 40% of the energy in the working week.

One potential reason for this could be due to the carrying out of trials of production of different

work orders. Although there could be several other reasons like idling of the machines,

compressed air losses, pumping losses or other machine losses. The efficiency can be increased

by better in-house energy management. One such framework is described which the company

can follow in order to assess and improve the energy efficiency in this regards.

Stama 1 Stama 2 Total

Energy use (kWh) 487,0 374,8 861,8

0,0

100,0

200,0

300,0

400,0

500,0

600,0

700,0

800,0

900,0

1000,0

En

ergy U

se (

kW

h)

Machine

Energy use during production week

Stama 1 Stama 2 Total

Energy use (kWh) 125,9 219,0 344,9

0,0

50,0

100,0

150,0

200,0

250,0

300,0

350,0

400,0

En

ergy (

kW

h)

Machine

Energy use during non-production week

39

Current working of energy management:

This section gives a overall picture of the working of energy management for Sandvik

Coromant in Gimo. Sandvik Coromant division have energy efficiency goals for each year.

Before every new year, the Energy and Sustainability engineer at the site reports environmental

actions to a global database as well as environmental data i.e. how much electricity, water,

waste, district heating, oil etc. Every quarter during the year, Sandvik Coromant reports status

on the energy efficiency measures on to the global databse which is being followed by the

global Environment Health and Safety (EHS) department. This department measures the total

energy efficiency for all of Sandvik Coromant sites together after each passing year. The energy

efficiency actions are taken in coordination with the global EHS department and the local

production or facility manager at the site. Sandvik Coromant in Gimo is deemed to be not

energy intensive, hence there is no specific energy management standard certified.

Suggested model of energy management:

An energy management system needs to be implemented which will identify and analyse the

energy flow. In addition. A responsible person must be appointed and given a suitable position

in the company. The work description of the person responsible for energy issues includes the

following tasks (Hessian Ministry of Economics, Transport, Urban and Regional Development,

2011):

1. Monitoring and organization of energy data collection

2. Performance of energy audits

3. Support for service providers (e.g. data acquisition, selection of measures)

4. Evaluation and selection of energy efficiency targets

5. In-house communication on the theme of energy

6. Monitoring and support during implementation of the measures

An example of an organization structure is shown in the chart below.

Figure 24 Organizational structure of Energy Management

40

Volvo CE is a good example to illustrate its strategy towards energy management and its

principles can be adopted. Its new strategy focussed in the following order: energy

conservation, imporved energy efficiency and renewable energy (Thollander, et al., 2020). The

three are described as follows.

• Energy conservation: It refers to not using the energy in the first place. E.g. turning off

equipment not in use, turning on equipment later at the start of production and turning

it off earlier and generally to use existing equipment in a smarter way to eliminate or

reduce the amount of energy used.

• Energy efficiency: It refers to investing in more energy efficiency equipment. E.g. new

electrical motors (like replacing IE2 motors with IE5), investing in energy recovery

and fundamentally investing in right size equipment.

• Renewable energy: It is the final step of the energy pyramid. It was termed CO2 neutral

but changed to renewable not to include nuclear energy and hence participating in

creating a global demand for renewable energy. It also highlights the need to start

prioritizing energy conservation, then on energy efficiency rather than purchasing solar

panels while wasting majority electricity produced by the solar panels.

Figure 25 Energy Pyramid at Volvo CE (Thollander, et al., 2020)

The strategy from the energy pyramid have resulted in several benefits (Ibid.). It helped to build

culture and behaviour where everyone in the factory is involved in energy conservation. This

takes time and to make sure all the employees are involved along with the different levels of

management in factory. Energy conservation is deemed to be low cost, thus it enables the

strategy to be self-funded. Energy bills are reduced and hence costs are reduced. Energy

conservation also reduces the size of future investments which is often overlooked. Without

making substantial capital investments, and trying to do low cost waste elimination

improvements, one gets to know the system better. E.g. reduced flow rates in a future

investment enables the use of smaller and less expensive pumps and motors. It is important to

note energy conservation is a never-ending journey. There needs to be some expectation from

the organization and leadership.

A KPI can be defined called as ‘relative idle electricity %’ which will allow the comparison

between the different factories despite variances in product, size, working hours etc (Ibid.). The

KPI can be defined as follows.

Relative idle electricity % = 𝑖𝑑𝑙𝑒 𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 (𝑘𝑊ℎ′𝑠 𝑑𝑢𝑟𝑖𝑛𝑔 10 𝑖𝑑𝑙𝑒 ℎ𝑜𝑢𝑟𝑠)

𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑒𝑙𝑒𝑐𝑡𝑟𝑖𝑐𝑖𝑡𝑦 (𝑘𝑊ℎ′𝑠 𝑑𝑢𝑟𝑖𝑛𝑔 10 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 ℎ𝑜𝑢𝑟𝑠)

Renewable Energy

Energy Efficiency

Energy conservation

41

Benchmark studies showed a good level of idle electricity for similar companies would be less

than 10% giving rise to potential for more challenging targets in the future (Ibid.).

Summarizing, the method proves that a large non energy intensive company can achieve

conisderable energy reductions through continous and systematic improvement activities like

Lean Energy.

Verein Deutscher Ingenieure (VDI) (English: Association of German Engineers) have

developed a standardized procedure to enable potentials to be realized within the framework

of an energy efficiency project called as ‘VDI Guideline 3922’, “Energy Consulting for

Industry and Business” (Ibid.). The purpose behind the guidline is to check energy use at

regular intervals and where necessary to carry out changes or renewals. A characteristic feature

of the procedure is the iterative process.

Figure 26 Procedure for implementation of energy efficiency measures (Hessian Ministry of Economics, Transport, Urban

and Regional Development, 2011)

First steps towards identifying energy efficiency potentials is to record the current state (Ibid.).

It is necessary to collect relevant data on energy supplies and energy use (e.g. technical

documentation on energy consumers, energy infrastructure and energy recovery) in order to

provide a strong basis for the description of current state. To create this basis, energy use data

must be assigned as carefully to their respective origins. For this, a balance scope will have to

be defined for the individual origins i.e. energy carriers therefore sensors or measuring devices

are installed if required. It is also necessary to classify the data by energy carrier like electricity,

heat etc. and category like lighting, ventilation etc. The balance scope can cover e.g. machines,

cost centers, production areas etc.

The next step is to develop proposals for increasing energy efficiency in the areas with energy

saving potential (Ibid.). When devising the measures, it is important to consider the following

set of approaches:

- Avoiding unnecessary energy use (e.g. reduction of idling losses)

- Reducing energy demand (e.g. use of energy efficient technologies)

42

- Reduction of transformation losses (e.g. reduction of distribution losses, increasing

utilization ratio)

- Implementing energy recovery (e.g. heat recovery applications)

- Use of regenerative energy sources (e.g. solar hot water systems)

It is imperative to observe the system in its entirety (Ibid.). There might be adverse effects on

the result. Hence, it is not possible to lay down an absolute order in which the procedure should

be carried out. Thus, the next step is to develop an overall concept. It is important to integrate

economic effects too when it comes to impact of the concept on technology and product quality.

Several alternatives should be worked out and compared in the manner of scenario analysis

(Computer aided simulation instruments). The relevant decision-making criteria are provided

here by key business figures and the energy saving potential. Other criteria could also be

profitability evaluation although it differs from one company to other. Examples of this are

security of supply, emission balance, anticipated new regulations etc. The final step is the

implementation and result checking, which should be carried out under the supervision of the

advisor. Continuous recording and maintenance of the energy related data enables assessment

at regular intervals of how far the goals have been achieved.

2. Pumps

A visit during the non-production week was made which was from 6th April to 10th April 2020

to investigate if there was idling of pumps in GVP3 facility. It was observed that almost all the

pumps were running resulting in idling losses. For instance, the energy use from the pumps

used for supplying cutting fluid to the STAMA machines (1 and 2) was calculated from the PI

System Explorer software. The production week data is from 10th February to 15th February

2020. The non-production week data is from 17th February to 21st February.

Figure 27 Pump energy use during production week in STAMA cells

STAMA 1 (M7

and M8 pump)

STAMA 2 (M7

and M8 pump)Total

Pump energy use (kWh) 123,9 99,0 222,8

0,0

50,0

100,0

150,0

200,0

250,0

En

ergy U

se (

kW

h)

Pump

Pump energy use during production

week

43

Figure 28 Pump energy use during non-production week in STAMA cells

The graphs indicate that there is relatively less energy use during the non-production week as

compared to production week. The approximate energy cost savings for the company could be

done by addressing the idling losses. Although, before deciding on a possible investment, the

existing pumps should be examined (Thollander, et al., 2020). One possibility could be that the

refurbishment costs would be lower than investment costs of a new pump. Say the pumps can

be refurbished by changing seals and bearings or maybe composite coated, or the impeller

diameter can be changed so that the pump fits better to the current operating point (Ibid.). Any

decision on renovation or new investment, the condition of electric motor driving the pumps

must also be examined and investigated.

Possible ways to reduce electricity requirements in pumps and improve the current working

system are mentioned as follows (Ibid.):

- Turning off unnecessary pumps

- Adjusting the dimensioning of pumps

- Installing an energy-efficient control of the flow (e.g. use of frequency converter or soft

start device avoiding throttle control)

- Installing an energy-efficient electric motor

- Eliminating the wear in the pumps

3. Compressors

Most of the compressors come in the form of packaged system in which the motor and the

compressor are in a full- or semi-hermetic enclosure (seal that is gas tight or impervious to gas

flow). Many compressor systems run in an efficiency range of only 5% to 10% (Waide &

Brunner, 2011).

STAMA 1 (M7

and M8 pump)

STAMA 2 (M7

and M8 pump)Total

Pump energy use (kWh) 13,1 0,1 13,2

0

2

4

6

8

10

12

14

En

ergy U

se(k

Wh

)

Pump

Pump energy use in non-production

week

44

Table 4 Example of losses in a compressed-air system, (Falkner & Slade, 2009)

Source of power loss Transferred “useful”

power (kW)

Power loss (kW)

Electrical power input 100 90 (heat)

Air from compressor 10 1 (e.g. filter pressure drops)

Treatment 9 1 (e.g. filter pressure drops)

Leakage 6 3 (leakage)

Distribution system 5.5 0.5 (e.g. excess pressure

drops)

Over-pressure 5.0 0.5 (heat)

Thus, it becomes imperative to calculate the efficiency of the compressors installed in tool

manufacturing companies. It would serve as a baseline for future investments if the compressor

efficiency is deemed to be low. There are two possible ways to measure the compressed air.

1. To calculate the compressor efficiency by taking the average power of the compressor

when the operations are not running which is divided by the average power of the

compressor when the operations are running. If the power of the compressor when the

operations are not running, it is difficult to know how much power the compressors are

using for compensation of leakages in the system.

2. To log the power of the compressor that is providing the machine with compressed air.

The data about total flow of compressed air the compressor produces is collected. The

ratio is calculated between the total flow and the flow going to the machine. This ratio

could be estimation of how much of the logged power in the compressor that can be

allocated to the machine.

With the above listed methods, one can have a rough idea about how efficient the compressor

systems are, while there is a need of further research and investigation about the compressors

considered in the case study. Electric servo or linear motors can serve as more efficient systems

which would replace many compressed-air and pneumatic control systems (Waide & Brunner,

2011). While some other measures on improving the energy efficiency in an industrial

compressed air system which the company can implement as per Thollander & Palm (2013).

These measures should be prioritized in the order that is presented below.

1. To examine alternatives to compressed air. Replacing as much as possible of the

compressed air demanding tools and processes.

2. To reduce or minimize the air leakages. This is an easy measure with short payback

period.

3. To use Variable Speed Drive (VSD) compressors.

4. To section the industrial compressed air system. Some machines would have different

pressure levels and different working hours.

5. To improve recycling of heat from the compressors. As seen from Figure 19, the energy

recycled in the month of August is low as compared to other months. This heat can be

used in the form of space heating purpose or in hot tap water.

45

5.2. Sustainable Value Stream Mapping

The below diagrams represent the value stream mapping of the four prioritize products i.e.

product A, product B, product C and product D. The yellow boxes in the left upper corner of

the diagrams shows the used carrier in the production process with different symbols ( Cutting

fluid- , compressed air- , cooling- , , electricity- , whereas the yellow boxes in the right

upper corner of the diagrams shows the units of the carrier used (Time- Minute, Material-

Grams, Energy- kWh). The description boxes below the product name indicates the different

operation information. This involves the uptime which considers the production to be

continuous. The raw material usage, lead time and the other carriers like electricity, cutting

fluid, compressed air, cooling water were represented along with the metrics. These all carriers

would not be quantified as all their data was not available, hence would be placed under the

operations indicating their use. The presence of the shapes indicates their use and absence

indicates not in use.

In the 2nd part of the diagrams represents the different process and the different carrier used i.e.

raw material removals, non-value added (lead time), value added (operation time) and batch

size. In the left bottom corner of the diagram shows the batch size, which is 100 for every

product, the total lead time, operation time, total energy, total material removal and the total

material added to a single product. The units used for the time, raw material and electricity are

placed in the top right corner.

In order to give a clear understanding to the reader, there are different color codes has been

used for each steps such as the line which indicates the operation time and lead time colored as

blue, the straight line with 4 boxes colored as green (represents the raw material uses) in the

production process. In the last part of the Sus-VSM diagrams shows the amount of carrier used

in different operation excluding the last operation (Packaging) as data was not available. The

upper blue lines represent the operations (value added) whereas the lower blue line represents

lead time (non-value added). The energy use for compressed air in Packaging operation has

been represented by a dash-dot line as it is based on rough assumption and may not indicate an

accurate picture. The Sus-VSM diagrams are shown below.

46

Figure 29 VSM diagram for Product A

Figure 30 VSM diagram for Product B

47

Figure 31 VSM diagram for Product C

Figure 32 VSM diagram for Product D

As the above products belongs to a same product family, they have some similarities in terms

of the carrier used and the raw material weight. The 1st machining operation only used two

carriers i.e. compressed air and cutting fluid as this is a dry operation. This machining operation

performs the complete milling operation. In the 2nd machining operation consumes all the

carrier, as this step performs multiple operation (taper turning, drilling, grooving, nulling etc.).

48

In the heat treatment operation. The 1st two operations are normally milling operation, so they

remove lots of material in each step. Which represents in a green line in the above diagrams.

The operation time is calculated by considering the production start and end time. The lead

time is calculated by the taking the end time and date of the 1st operation and the starting time

and date of the 2nd operation. For few of the products the lead time is high due to some

maintenance work, tool failure and the closing of the production plant. The heat treatment

operation (3rd operation) uses compressed air, cooling water and the electricity with a standard

operation time. But unfortunately, in this study the researchers failed to collect the energy

invoices due the COVID-19 pandemic. So, it’s bit difficult to analyze the electricity use for

that operation.

The lead time is calculated by the taking the end time and date of the 1st operation and the

starting time and date of the 2nd operation. For few of the products the lead time is high due to

some maintenance work, tool failure and the closing of the production plant. The heat treatment

operation (3rd operation) uses compressed air, cooling water and the electricity with a standard

operation time. But unfortunately, in this study the researchers failed to collect the energy

invoices due the COVID-19 pandemic. So, it’s a bit difficult to analyze the electricity use for

that operation. The last step is the packaging part, which involves marking, oiling, assembly,

inspection and stickering of the products. As the involvement of robots were there, so this

operation used compressed air and the electricity. From the above diagrams the operation time

for last phase is lesser as compared to the other three steps. This step adds around 0.06 gm of

extra weight to the product which is similar to the weight addition of the heat treatment step.

From above diagrams shows that the total lead time for product A is 9798 minute and the total

operation time is 2662 minute, the total material removal is 0.915 kg and the material uses is

0.12 kg. In product B, the total operation time is 266-minute, lead time is 9798 minutes. The

raw material removal for product B was 0.918 kg. Only 0.12 kg of extra material was added to

all the four products in the packing and the heat treat operation. For product C, the total

operation time is 8122-minute, lead time is 3805 minutes. The raw material removal for product

C was 0.756. For the 4th product (Product D), the total operation time is 7774 minutes, the lead

time is 29993 and the material removal rate is 0.897 kg from the first two machining operations.

The metrics other than lead time have been merely mapped to gain an understanding of the

current state. Regarding the lead time, Product A has the least which implies it is doing

relatively good while Product B, Product C and especially Product D have a high lead time. As

the products belong to the same family of turning tools, ideally the lead time should be close,

but it is not the case here.

5.3. Energy Cost Tool

With the help of the Energy Audit and Sus-VSM methods, the data for the cost tool is made

available. The energy cost tool is split into two excel sheets – tool and data. The tool sheet

consists of the actual energy cost tool whereas the data sheet consists of the data required as

input to tool. It was not possible to collect/calculate all the values in the data sheet due to

limitations stated previously. It is hoped that the missing values would be inserted into the data

sheet in the future.

The Tool sheet is further divided into Production and Facility section. The M7 and M8 pumps

are assumed to be the pumping energy requirement for cutting fluid. The electricity use in

Machining 2 operation was made for another equivalent product of the same dimension as the

49

original four products. Hence it is assumed to be the same value for all the four products. The

energy use per product for compressed air in Packaging operation is roughly assumed to be

directly proportional to the number of connecting pipes and its equivalent area. The gas used

in the Heat Treatment was not monitored.

To make the tool more user friendly, tutorial boxes are placed wherever there is an input

required. Table 3 in the Tool sheet assumes equal energy use per machines. The emissions from

production and support processes are summed up at the end giving the total (kg CO2eq). A

“Clear All” button is also added at the bottom of the tool to facilitate the user. By clicking this

button, the fields which require input from the user are cleared and is ready for new values. A

reference chart is also provided in the Tool sheet so that the user knows which energy carrier

is being used in which operation. It considers electricity, cutting fluid and compressed air.

Table 5 Reference Chart for the Tool sheet

Operations Electricity Cutting Fluid Compressed Air

Machining 1 ✔ X ✔

Machining 2 ✔ ✔ ✔

Heat Treatment ✔ X ✔

Packaging ✔ X ✔

Machining 1 ✔ X ✔

The * symbol is the assumed value for the GHG emission factor. The GHG emission factor for

electricity and district heat is taken from the source (Johnsson, et al., 2019). In the Data sheet,

the values are represented in terms of energy per piece for the energy carriers for the four

products. Figure 33 and Figure 35 demonstrates the energy cost tool working. This is not the

actual representation as some of the values are missing currently. In the example shown in the

following figures, ‘100’ number of products have been placed for Product A. The missing

values for energy carriers have been placed by ‘1’ kWh. Total energy use in Industrial area 1

is placed by ‘100’ kWh and the total district heat supplied is placed by ‘1000’ kWh. This has

been done to exemplify how the tool would work in the future when all the values are inserted.

It does not show an accurate picture as the numbers have been arbitrarily placed in the tool.

50

Figure 33 Energy Cost Tool: Tool Sheet

51

Figure 34 Energy Cost Tool: Data Sheet

52

Figure 35 Output Report Sheet

53

5.4. Energy Performance Indicators (EnPIs)

There are several Energy Performance Indicators (EnPIs) used to track and monitor the energy

use in the STAMA machine cells. The list of the current EnPIs is shown below.

Table 6 List of current EnPIs used in STAMA cells

Sr. No. EnPIs Characteristic

1. Power consumption by M7 pump (W) Absolute

2. Power consumption by M8 pump (W) Absolute

3. Energy use by M7 pump (kWh) Absolute

4. Energy use by M8 pump (kWh) Absolute

5. Total Power consumption (W) Absolute

6. Energy Mode Savings (%) Ratio

7. Power consumption per hour (W) Absolute

8. Power consumption per minute (W) Absolute

9. Total energy use (kWh) Absolute

10. Total energy use per piece (kWh) Absolute

By analyzing the literature paper, (Kanchiralla, et al., 2020) there were several EnPIs which

were studied and further suggested. The EnPIs shown below are the indicators which could be

developed and added into the PI System Explorer software through current available data.

Table 7 List of suggested new EnPIs which can be developed through available data in STAMA cells

Sr.No. EnPIs Characteristic

1. Peak demand in a month (kW) Absolute

2. Electricity use (kWh) during peak hours Absolute

3. Total energy use (kWh)/tonne of production Ratio

4. Total energy use (kWh)/hour of production Ratio

5. Total energy use per cycle (kWh) in combination with

article and used methods

Absolute

6. Total production time in hours (for one order)/article Absolute

7. Total energy use of energy carrier (kWh) in

combination as well as separate/article *

Absolute

8. Total energy use (kWh) in Eco-mode * Absolute

9. Total energy use (kWh) in idle mode * Absolute

10. % of total energy use at idle (kWh) vs total energy use

(kWh)

Ratio

*The additional information about the selected EnPIs are discussed as follows.

• The EnPI ‘Total energy use energy carrier (kWh) in combination as well as separate

/article’ can be used to evaluate which article uses a lot of the energy carrier in that

operation. The energy carrier could be cooling water, electricity, compressed air etc.

For example, it would help in investigation for an article using a lot of cutting fluid.

This will help the company to develop new methods which would use much less of the

energy carriers.

• The EnPIs ‘Total energy use (kWh) in Eco-mode’ and ‘Total energy use (kWh) in idle

mode’ can be used to evaluate how much energy is being lost (idling) or saved (Energy

saving mode or Eco-mode). These will require indicators if anything shifts, for instance

if compressed air is being used more than the normal value.

54

It may be noted that the EnPIs listed in Table 5 and Table 6, only list the indicators which are

currently in use and could be developed through available data respectively. While these

indicators are used for the STAMA machine cells at present, these may also be used in other

machine cells in the industry. This would require connecting sensors which are presently

unavailable. It is important to address that these EnPIs cater to the production processes only.

There could be several factors like different production technique, different raw material,

different amount of cutting fluid or compressed air used etc. thereby affecting the energy

performance. Apart from the EnPIs suggested in Table 5 and Table 6, there were new proposed

EnPIs in Table 7. These new proposed EnPIs would require additional data in order to

implement and to be used in the software.

Table 8 List of suggested new EnPIs in STAMA cells

Sr.No. EnPIs Characteristic

1. CO2 emissions (tonne)/ energy use in process (kWh) Ratio

2. Total energy savings (kWh) from EEM/year Absolute

3. Actual energy use to actual output/rated energy use

to rated output

Statistical

4. Machine energy efficiency (%) Ratio

5. Instantaneous energy efficiency (%) Ratio

6. Cooling demand for cutting fluid (kW) Absolute

*The additional information required to develop new EnPIs is listed as follows.

• The EnPI ‘CO2 emissions (tonne)/ energy use in process (kWh)’ would require the

calculation of CO2 emissions by identifying the emission factor in (t CO2)/kWh.

• The EnPI ‘Total energy savings (kWh) from EEM/year’ would require the quantitative

evaluation of the energy efficiency measures adopted in the production process.

• The EnPI ‘Actual energy use to actual output/rated energy use to rated output’ requires

the data of actual energy output, rated energy use and rated energy output.

• The EnPI ‘Machine energy efficiency (%)’ use Specific energy use to evaluate and this

requires one additional parameter, total volume of removed material (Vmaterial) while the

total energy use of the machine tool (E) in kWh is available (Lirong, et al., 2016). This

can be calculated as follows:

Specific energy use = 𝐸

𝑉𝑚𝑎𝑡𝑒𝑟𝑖𝑎𝑙

• The EnPI ‘Instantaneous energy efficiency (%)’ requires two additional parameter,

material removal cutting power Pcut(t) and the machine input power P(t). This can be

expressed as:

Instantaneous energy efficiency (t) = 𝑃𝑐𝑢𝑡(𝑡)

𝑃(𝑡)

• The EnPI ‘Cooling demand for cutting fluid (kW)’ requires the specific heat capacity

of the cutting fluid (Cp) in J/kg ̊ C, mass flow rate of the cutting fluid (m) in kg/s, inlet

(Ti) and outlet temperatures (To). This can be formulated as:

Cooling demand for cutting fluid = m*Cp*(To-Ti)

The EnPIs enlisted in the literature (Kanchiralla, et al., 2020) for the support processes were

also studied and investigated. The general EnPIs are the ones which can be used for all the

55

support processes like lighting, pumps, ventilation and so on, while there are a couple of EnPIs

specific to the compressors. At present, there are limited/no sensors monitoring the support

processes. Thus, it requires capital investment first to purchase and install the appropriate

sensors for energy monitoring. The EnPIs for support processes are shown below and are self-

explanatory.

Table 9 List of suggested new EnPIs for support processes for the industry

Sr.No. Unit Process EnPIs Characteristic

1. General for

support

Energy use during peak hours (kWh) Absolute

Total energy savings (kWh) from

EEM/year

Absolute

CO2 emissions (tonne)/Energy use in

process (MWh)

Ratio

Total energy use (kWh) Absolute

2. Compressed

Air

Energy used (kWh)/air supply (m3) Ratio

Leakage rate (Compressor Free Air

Delivery (m3/h) X avg load time/total

operation time (h))

Statistical

5.5. Interpretation of Social Sustainability

Social sustainability is the least quantifiable dimension when compared to environmental and

economic sustainability (ADEC Innovations, 2020). In order to answer the 3rd research

question this survey was carried out in the case company with 10 questions (Appendix 3). Out

the 54-sample size there was around 33 participants who answered the question. This segment

decries the analysis of the participants response. Table 10 represents all the statements used the

in the survey and the total number of responses given by the 33 participants.

56

Table 10 Results of social sustainability survey

Sr

no.

Statements I

agree

I somewhat

agree

I somewhat

disagree

I

disagree

1 Sandvik Coromant in Gimo is

actively working with

sustainability.

23 10 0 0

2 Sandvik Coromant in Gimo have

a way of working that enables

me to work in a sustainable way

with regard to psychosocial

health and well-being.

12 20 1 0

3 I have the possibility to educate

and make a career at Sandvik

Coromant in Gimo if I desire to.

18 14 1 0

4 My workplace is adapted for all

employees to have good

ergonomics.

20 10 3 0

5 In my workplace I can

experience loud noises.

8 10 12 3

6 I feel safe working at Sandvik

Coromant in Gimo with regards

to injuries and accidents.

25 8 0 0

7 At Sandvik Coromant in Gimo

all employees are treated as

equals no matter of gender,

background or nationality.

25 8 0 0

8 At Sandvik Coromant in Gimo

gender equality is important.

19 11 3 0

9 At Sandvik Coromant in Gimo

we work with diversity and

inclusion.

17 16 1 0

10 I believe Sandvik Coromant,

Gimo is working towards

improving resource efficiency

and reducing waste.

21 11 1 0

For instance, the first question was ‘Sandvik Coromant in Gimo is actively working with

sustainability’. Most of the participants agree with this statement, out of 33 participants 23

people completely agree with the statement and 10 people are ‘somewhat agree’ with the

statement. The same is applicable to all the other statements in the survey.

57

Table 11 Social Sustainability score matrix

Sr

no.

Statements "I agree"

score

"I somewhat

agree" score

"I somewhat

disagree"

score

"I disagree"

score

Average

score

1 Sandvik Coromant in Gimo is

actively working with

sustainability. 92 30 0 0 3,69

2 Sandvik Coromant in Gimo have a

way of working that enables me to

work in a sustainable way with

regard to psychosocial health and

well-being. 48 60 2 0 3,33

3 I have the possibility to educate

and make a career at Sandvik

Coromant in Gimo if I desire to. 72 42 2 0 3,51

4 My workplace is adapted for all

employees to have good

ergonomics. 80 30 6 0 3,51

5 In my workplace I can experience

loud noises. 32 30 24 3 2,69

6 I feel safe working at Sandvik

Coromant in Gimo with regards to

injuries and accidents. 100 24 0 0 3,75

7 At Sandvik Coromant in Gimo all

employees are treated as equals no

matter of gender, background or

nationality. 100 24 0 0 3,75

8 At Sandvik Coromant in Gimo

gender equality is important. 76 33 6 0 3,48

9 At Sandvik Coromant in Gimo we

work with diversity and inclusion. 68 48 2 0 3,57

10 I believe Sandvik Coromant,

Gimo is working towards

improving resource efficiency and

reducing waste. 84 33 2 0 3,6

As stated in the methodology chapter, “I agree” was given a rating of 4, “I somewhat agree”

was given a rating of 3, “I somewhat disagree” was given a rating of 2 and “I disagree” was

given a rating of 1. The average score of each statement was computed at the end. As seen from

Table 10, almost all the statements have a high score out of 4 except for statement five. In this

statement, lower score expresses satisfaction as less noise is good for the working environment.

Statements one, six and seven have relatively high score than the rest where the company’s

sustainable, health and safety and no discrimination values are reflected in a positive manner.

Statements two, three, five, eight and nine have relatively less score. The score of these

statements show that there is a scope of improvements in those areas. The following describes

the description of statements along with the improvement suggestions in Table 12.

• Statement two: This statement reflects the importance of the implementation of

sustainability with regards to the physical health and wellbeing.

• Statement three: It reflects the importance of education inside the organization.

• Statement four: It reflects the importance of ergonomic conditions in the workplace.

Primarily, this statement was more targeted towards the employees working closely in

the production areas.

58

• Statement five: This statement has the importance of impact on the employees due to

loud noise at the workplace. As 50% of the participants works in the production line,

so there are experiencing load noise.

• Statement eight: It reflects the importance of gender equality which suggests that

Sandvik Coromant needs to strive for better balance in all its departments at site.

• Statement nine: It shows the importance of diversity which suggests that Sandvik

Coromant needs to strive for better balance at site.

Table 12 Improvement suggestions in social sustainability survey

Statements Improvement 1 Improvement 2 Improvement 3 Improvement 4

Statement two Promoting mental

health and social

wellbeing (European

Commission, 2014):

1. Being valued at

work

2. Being able to make

decisions on issues

that affect employees

3. Having all the

necessary resources

that employees need to

do the work

4. Having a job that is

well designed (i.e. not

overloaded)

5. Having work that is

organized better in

terms of work

schedules and time

offs

Social aspects of

workplace:

1. Social support

where the workmates

can help individuals

share, cope with and

overcome personal

issues.

2. Coping skills as

social interaction in

the workplace can

directly or indirectly

provide opportunities

to learn effective

coping skills.

3. Material support

where workplaces

provide resources in

terms of monetary

income.

- -

Statement three Encouraging more

educational and self-

development programs

within the company

for its employees.

Make the necessary

education better

accessible than it is

presently.

- -

Statement four Work surfaces should

be the right height of

the task and the

employee to eliminate

bending or reaching.

Frequency of tools and

parts should be stored

within easy reach or

location.

To avoid reaching,

extension poles and

adjustable height

platforms could be

used.

Utilizing sit/stand stool

can reduce the amount

of time employees are

standing.

Statement five Installation of modern

machines which

produces less noise.

Covering the machines

cells with sound-proof

glasses.

- -

Statement eight Need to increase

hiring of female/other

gender employees as

most of the working

professionals are male.

Should introduce

programs to encourage

more female

professional or

graduates.

- -

Statement nine Hiring of candidates

from different

countries with

multicultural work

background as most of

the working

professionals are from

Sweden though

Sandvik Coromant is a

global organization.

- - -

59

In order to implement this, the authors argue that tool manufacturing industries need to see first

the organization as a social framework in itself and second how they are installed in other social

frameworks (Fobbe, et al., 2016). Also, they have to set up basic conditions and improve their

insight to have the option to disguise social sustainability before actualizing instruments and

activities that lead to social sustainability (Ibid).

6. Discussion This section outlines, sum up and propels the investigation section through a conversation as

per the research questions. The discussion raises why certain things were analyzed and why

some were not alongside how they were applicable for the study. Additionally, the conversation

part treats the analysis, the confinements, and recommended future work within the same area.

Also, this segment, the analyzed empirical data and initial theoretical findings will be analyzed

in relation to each other to ultimately answer the research questions. More specifically, value

stream method (VSM), energy audit, energy cost tool implementation, EnPIs framework and

social sustainability will be applied on the empirical case and an analytical relation with the

literature will be discussed. Finally, this section will also give a basic introduction for future

research.

Research question 1

In this study the 1st research question is ‘How can energy use be studied, mapped and its energy

efficiency be improved in a tool manufacturing?’. This 1st research question was broken down

into two explicit parts in order to achieve the desired results. For the energy study, bottom-up

energy audit was implemented and for energy mapping, Sus-VSM methodology was adopted.

The audit process helped to understand and comprehend the production process ongoing for

the selected products through surveying phase. The structure of the audit was adopted like the

one developed by (Rosenqvist, et al., 2012) i.e. survey, analysis and efficiency measures. The

bottom-up approach was deemed necessary in order to get the overall picture while the top-

down audit approach would have been difficult to implement. It may not have provided the

desired results for this study. The Sus-VSM method developed by (Faulkner & Badurdeen,

2014) can be considered as relatively new. The application to case studies was limited to

satellite production line, bar fabrication and mortar fin production. This study serves as an

extension to its methodology, barring a few changes to the metrics and the original framework.

The study demonstrates a correlation between the two methods which was found missing in

the previously identified literature. The study provides a new insight into the relationship

between the two methods (audit and Sus-VSM) and how it can complement each other.

Due to the limitations enlisted by the company and the Covid-19 scenario, the study has been

affected. Due to the lack of data, the results cannot exactly confirm which energy carrier like

compressed air, cutting fluid, electricity etc. affects the energy use most in the production line.

The energy measuring was limited till heat treatment operation thus excluding packaging

section. It was beyond the scope of the thesis to study the support processes like lighting,

ventilation, pumping etc. in detail. The energy balance diagram thus could not be created. The

energy efficiency measures are merely stated qualitatively as the quantification of energy

savings is quite difficult. Though the measures are based on the previous literature and

research, they are likely to have a positive outcome on energy efficiency. This will in turn

influence positively on the economic sustainability of the company. The majority values in the

60

Sus-VSM are termed as missing thus making it difficult to grasp the overall picture of the

manufacturing process of the products.

There is a need to determine the missing values in the Sus-VSM to fulfill the need of knowing

which energy carrier uses the most energy in the future. This can be done through a thorough

energy measurement in-house or with the help of an external audit. This will help to fill in the

missing values in the diagrams. Further research is needed to see if this new established

relationship between audit and Sus-VSM could be extended and implemented in other large-

scale industries or even SMEs.

Research Question 2

The 2nd research question was ‘How can EnPIs and energy cost tool be developed and

implemented in a tool manufacturing industry?’. The results support and build on the studies

conducted by (Kanchiralla, et al., 2020) and (Johnsson, et al., 2019) and extended it to a tool

manufacturing industry. Several of the suggested EnPIs in this study share several similarities

with their studies for example Peak demand in a month (kW) in Table 7. The identified three

tables of new EnPIs will assist the company to closely monitor the energy use for its support

and production processes. It is more likely that Table 7 EnPIs could be integrated into the

software system readily as they require minimum additional information. While Table 8 and

Table 9 EnPIs would require a greater time frame in order to evaluate and integrate. The

categorization of system boundaries is in accordance with the study conducted by (Sommarin,

et al., 2014) which divide into overall, support process and production process specific figures.

The results of this study are based on the categorization into support and production processes.

Studies show that the comparison of EnPIs in the industry is complex due to different energy

end-use, undefined boundaries and heterogenous products (Bunse, et al., 2011). Tool industry

generally have homogenous products, thus the suggested EnPIs in this study could potentially

be extended for other tool manufacturing industries. The limitation of this study is that the wide

range of products in the manufacturing industries makes it difficult for more detailed EnPIs.

Further research in this area could be to develop EnPIs at sub-unit process level.

The manufacturing costs are not only limited to the production, but also other parameters like

cost of staff, support processes, materials etc. Thus, the cost tool developed tried considering

both the production section as well as facility section. While (Nord, et al., 2015) considered

operation time in their model, the cost tool developed in this study excludes this parameter but

retains the type of operations and carrier. The tool simplifies the energy cost calculation on

energy use (kWh) per piece for the production section and for the facility. The combined energy

use from the production and facility will provide a rough estimation on the carbon footprints

from the manufacturing of the products. While there are several cost tools models which have

been developed with a high degree of complexity involved, the cost tool in this study strives to

simplify as much as possible. This is needed so that the tool can widely be used among the

employees who may/may not have knowledge about energy use and related terminologies in

general.

The cost tool data sheet has majority of the values missing which is a major limitation. The

tool as of now can be deemed difficult to use due to this reason. As mentioned previously, the

cost tool is limited to production and facility. Further work in this area involves the evaluation

of cost related to materials, cost of staff and so on. This will provide and depict an accurate

61

picture of the total cost involved in the product’s manufacturing apart from energy use. It

remains to be seen if this simplified framework can be generalized for other manufacturing

industries as well. The tool can help and facilitate in evaluating the carbon footprints from their

production line. This data can further help and support energy efficiency measures thereby

reducing the emissions.

Research Question 3

The 3rd research question was ‘How can social sustainability be measured and improved in a

tool manufacturing company?’. The social sustainability is an important aspect in an

organization. In order to answer the 3rd research question, the authors decided to do a survey

among the employees working with three different departments in the case company. The

sample size targeted was 54 and the responses received were 33, which is about 61%. These

were explicitly perused to a contextual analysis as the principle objective was to see how social

sustainability in the organizational context could be executed in a proper manner. The

congruity of literature and the outcomes from the 3rd research question drove the researchers

to the suspicion that their conclusions from the RQ 3 were likewise appropriate to different

MNCs. As the case study company was a typical multinational organization, it works in several

countries and cultural settings.

The key discoveries from the present truth of the case study organization were an absence of

comprehension on what social sustainability implied and whether it was critical or essential.

Also, there was a missing review of approaches and an ineffectual structure with regards to

social sustainability (Boström & Magnus, 2012). These outcomes affirmed for the most part

what the researches had explored in the current literature on the subject.

From the survey, there are few factors where the case company need to focus in order to

implement social sustainability. The social sustainability matrix gives a good interpretation of

the results from the survey. This gave rise to explore the potential to improve regarding

statements two, three, four, five, eight and nine. The case company need to work on the

diversity, gender quality, continuous learnings within the company and loud noise created by

the machines. These are the few major areas need to be considered and likewise could be the

applicable for other MNCs. The way that fact all respondents had an alternate comprehension

of social sustainability was additionally in accordance with the writing depicting social

sustainability as increasingly hard to get a handle on (Boström & Magnus, 2012). Hence, there

was a need to begin from the essential comprehension of the idea of social sustainability before

its implementation. The limitation in this case is the number of people surveyed. As Sandvik

Coromant, Gimo has about 400-500 employees at Industrial area 1, the sample size considered

is very small. The survey could be extended to the whole organization in future and not only

site Gimo. This is to see where exactly they are in social sustainability context to gain a deeper

understanding of this pillar.

62

7. Conclusion This study gave a small benefaction to the academic research work in order to understand the

current and future benefits and challenges in implementing Sustainable Manufacturing in tool

manufacturing industries. This study could also be helpful in Sustainable business in different

MNCs. From this research work, the reader could learn that the implementation of sustainable

manufacturing is an important initiative, which will help the organizations to improve their

productivity by reducing cost, waste and environmental impact, thus giving a positive effect

on the triad of sustainability: Economic, environmental, and social dimensions. Today we are

living in the fourth industrial revolution era, where many SMEs and MNCs are dealing with a

rapidly growing economy and environmental challenges. Therefore, the survival of the existing

and new companies depends on their ability to address these challenges. Rather than

considering this as an obstruction to their development, the organizations should accept this as

an opportunity and find ways to gain competitive advantage from their sustainability efforts.

The research aimed to look at all three dimensions of sustainability for a family of products in

a production line and to see how far the case company i.e. Sandvik Coromant has come in the

sustainable manufacturing dimension. Furthermore, the research aimed to create a tool in order

to evaluate environmental sustainability concerning energy use and CO2 emissions. Based on

a quantitative and qualitative analysis of the three sustainability dimensions, it can be

concluded that to achieve sustainable manufacturing it’s important to look each of the three

aspects.

The results indicate that bottom-up energy audit and Sus-VSM can complement each other to

improve the environmental sustainability of tool manufacturing company. Although there are

relatively few journal articles which cover the bottom-up energy audit method, the thesis study

implemented concept of unit process from the research article (Sommarin, et al., 2014) and the

overall audit approach from (Rosenqvist, et al., 2012). The benchmarking approach used in this

study considering Volvo CE regarding energy management from the article (Thollander, et al.,

2020) could be beneficial for other tool industries too. This will help to evaluate what is

currently lacking in terms of the approach, policy or management in their present-day set-up.

Regarding the EnPIs and energy cost tool development, results indicate both could be

developed to support the economic as well as environmental sustainability dimensions. The

results from the journal article by (Kanchiralla, et al., 2020) have been extended to tool

manufacturing companies. While, the cost tool is relatively simple in terms of its design, the

parameters considered vary from the tool developed by (Nord, et al., 2015) and also differs in

terms of its purpose. The simplicity of the design in this study makes it more extensible and

adaptable to other tool industries with some modifications to evaluate energy use and CO2

emissions.

Most of the literature indicated that, the social sustainability is an emerging challenge for many

organizations in future. This study with the help of 3rd research question showed that there was

an absence of direction and structure on the best way to move towards social sustainability in

a vital manner among companies. This indicates that, there is a requirement for a general

direction on how social sustainability can be effectively achieved. Out of the ten statements of

the survey, there could be improvements made in areas concerning statements two, three, four,

five, eight and nine correlating to: diversity, gender quality, continuous learnings within the

company and loud noise created by the machines.

63

Theoretical and managerial implications:

This thesis gives an outlook about all the three sustainability dimensions – environmental,

economic and social in terms of sustainable manufacturing. This study will benefit individuals

or groups that are interested in energy use in tool manufacturing companies. This can also serve

as a reference for people who would like to conduct studies linking an energy audit process

with Sus-VSM perhaps for large-scale industries in other sectors. It assesses social

sustainability of working environment, developed and suggested EnPIs for tool manufacturing

industry. It also developed a new simplified cost tool, which was found missing in the previous

literatures and could be implemented with some modifications in its design in other companies.

8. Future Scope This study has out lined the vital comprehension on the needs, techniques of implementation,

and techniques for evaluations in achieving a sustainable manufacturing framework in a tool

manufacturing company. Furthermore, the three significant stages to accomplish and

consequently effectively actualize the desires for manufacturing frameworks with

sustainability characteristic features. Such as, research, development, and commercialization,

have additionally been featured in the current setting i.e. social sustainability. The significant

research gap lies in the identification of powerful execution procedures and the ideal needs.

Therefore, a lacuna despite everything exists for a point by point rules that can at last guide in

characterizing the related reasonable structure and sustainable manufacturing practice

techniques (Zindani, et al., 2020).

This segment speaks to various proposals concerning shortening lead time, energy cost and so

forth are talked about. These suggestions depend on lean standards, Design for environment

(DFE) and design for manufacturing (DFM), as explained on in the "Toyota way". Every

proposal's area will first quickly portray the issue, trailed by some potential solutions for

development.

Audit and Sus-VSM- It was not possible to grasp an overall picture of the energy use of the

entire production line due to limitations. The future work in terms of energy audit could be to

have every necessary value regarding the energy carriers used in the different operations. This

will not only aid in fulfilling the Sus-VSM diagrams but also help to evaluate the energy costs

and carbon footprints through the energy cost tool in the future. The energy efficiency measures

proposed in the study need to be further investigated and quantified as to how much energy

savings it would result if implemented. There is a further need of research to determine if the

established relationship between Sus-VSM and energy auditing can induce fruitful results in

terms of enhancing sustainable values within an industry. And, if it could be generalized and

extended to other industries apart from tool manufacturing.

Lessening lead time is a profitable aim on commerce entrepreneurs. Not exclusively does a

shorter lead time mean less time spent trusting that stock will show up, however it likewise

takes into consideration more prominent flexibility (TradeGecko, 2018). From the previous

analysis at the case company, after the 1st machining operation, the product had to wait

approximately 2 days for the next operation i.e. machining operation 2. This duration for the

waiting varies from different operation. Such delay caused by various issues like tool breaking,

maintenance work, lack of machine operators, multiple products for the same operation at same

time period and lack of proper product operation flow. Instead of changing tools frequently,

64

the operators should manufacture the products from the same product family which may results

less down time. Another improvement in terms of the production planning, from the Sus-VSM

diagram is that the lead time is varies from operation to operation and product to product. In

order to reduce the lead time, they should plan the complete operation of a single product

continuously by considering a standard lead time.

Energy cost tool – The tool developed in this study has been considered based on the production

taking place in the factory. The system boundary could be expanded beyond this and consider

the supply chain of the raw material as well as finished product. The raw material refers to the

machining energy use for the raw blanks which are used as an input to the Machining 1

operation in the factory. While the finished product involves the transportation emissions from

the factory to the desired destination. The energy use and its equivalent GHG emissions could

be integrated into the tool resulting in the complete overview. Further research in this area

could be to display it in the form of a dashboard system which would monitor all the

information in real-time. This will be the ideal case for the company to showcase its

sustainability performance and would be a worthwhile contribution to its stakeholders as well

as customers.

EnPIs -The development of the proposed EnPIs are hindered by the barriers mentioned in the

study by Andersson and Thollander (2019). To overcome these barriers related to EnPIs, tool

manufacturing industries could be encouraged to engage in joint research collaborations. While

increasing awareness of sustainability among the customers and key stakeholders could require

the company to adopt EnPIs to closely monitor its energy use. This will further help to develop

and increase energy efficiency within processes falling under different system boundaries

thereby reducing carbon footprints. The suggested new EnPIs require further research as to

how they could practically be integrated into the system while having the results in this study

as the baseline.

Social sustainability- Most of the findings from the case study on what is expected to actualize

social sustainability in a tool manufacturing company. Due to the lack of groundwork in the

case company about social sustainability, the researchers failed to develop more efficient

guidelines for implementation of social sustainability. Subsequently, there is requirement for

further research within the case company and other tool manufacturing industries. The

researchers suggest that future research should begin with the genuine guidelines for the

implementation of social sustainability.

65

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Appendix

Appendix 1. PI System Explorer

73

Appendix 2. Semi-structured interview template

74

Appendix 3. Social sustainability survey template

75

Appendix 4. VSM Calculation

Table 13 Material removal

The above table represents the total material removal and added in the all operation. From the

analysis, the Machining 1 process removes most of the material from the raw material block.

It’s the same for all four products. The 1st two operations removes most of the material from

the raw products and the last two operations adds extra material to the finished products, which

is comparatively very less. Because the heat treatment and the packing operation are the final

operations for the complete products.

Product Volume

Blank

Wt.

in kg

Volume

After

Machining 1

Wt. in

kg

Volume

After

Machining

2

Wt. in

kg

Wt. in kg

after Heat

treatment

Wt. in kg

after

Packaging

Product A 182938,05 1,44 105251,66 0,83 89988,81 0,71 0,05 0,05

Product B 182938,05 1,44 102850,42 0,81 89332,89 0,70 0,05 0,05

Product C 159469,52 1,25 100430,32 0,79 82400,26 0,65 0,05 0,05

Product D 182938,05 1,44 102819,76 0,81 90265,09 0,71 0,05 0,05

76

Table 14 Operation and lead time

The above table represents total operational time for each operation and the lead time in

minutes. As stated in the literature section here the calculation is done for the operational time

by comparing the end date & time of the previous operation and the start of the next operation.

Here in this study, most of the operational time and the lead time varies from product to product

due to some losses such as the maintenance work, tool breakdown and the order sequence. But

at the same time in the packaging part the operational time is very less as compared to the lead

time.

Product

Name

Machining

1 (min)

Lead

time

(min)

Machining 2

(min)

Lead

time

(min)

Heat Treatment Lead

Time

(min)

Packaging

Product A 508 1348 1305 4847 526 3603 323

Product B 4774 882 753 1881 218 9872 180

Product C 5325 1835 1781 1773 355 197 661

Product D 558 27562 428 1158 315 1273 6473