IDENTIFICATION AND EXTRACTION OF FACTORS AFFECTING ...

JOURNAL OF CRITICAL REVIEWS

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IDENTIFICATION AND EXTRACTION OF FACTORS

AFFECTING MAINTENANCE STRATEGY SELECTION WITH

39 PARAMETERS OF TRIZ APPROACH USING META-

SYNTHESIS

MOHAMMAD AMIN MORTAZAVI1, ATEFEH AMINDOUST

2*, ARASH SHAHIN

3, MEHDI KARBASIAN

4

1 Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran

2* Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran

3 Department of Management,University of Isfahan,Isfahan,Iran

4Faculty of Industrial Engineering, Malek-Ashtar University of Technology, Shahinshahr, Iran

*Corresponding Author

ABSTRACT

There is a large body of literature on maintenance subject driven by its significance. In this research, the components of effective

selection of maintenance tactics from a new perspective and innovative according to Altshuller's parameters are identified,

extracted and classified in the TRIZ inconsistency matrix. The present qualitative meta-synthesis study sought to explain the

components of different dimensions of maintenance strategies in order to identify, explain, and define the factors affecting

maintenance strategy selection thorough related literature. For this purpose, the findings of previous studies were analyzed using

meta-synthesis. Then, the components affecting maintenance strategy selection were extracted and identified through the seven

steps and classified in 26 concepts and 59 codes. Organizations which intend to apply maintenance strategies can gain a better

insight about benefits of using Altshuller's parameters in TRIZ matrix. Given the nature of the TRIZ inconsistency matrix in

resolving inconsistencies among the 39 Altschuller parameters, it is possible to resolve the inconsistencies among the factors

affecting the selection of maintenance and repair tactics through this matrix and to always propose an appropriate solution to the

existing problems. Maintenance managers are able to select the appropriate maintenance and repair tactics in industrial units.

Keywords: Maintenance strategies; Qualitative methods; Meta-synthesis; TRIZ Contradiction matrix

Purpose: The paper aims to identification and extraction of factors affecting maintenance strategy selection with TRIZ approach

using meta-synthesis

Design/methodology/approach: A meta-synthesis approach was conducted by adopting ―Rousseau and Sandoski‖ seven-step

method. Findings: The findings of previous studies were analyzed using meta-synthesis. Then, the components affecting

maintenance strategy selection were extracted and identified through the seven steps and classified in 26 concepts and 59 codes.

Research limitations/implications: The main limitation is that this research does not provide criteria and measures to assess the

benefits of factors affecting maintenance strategy selection.

Practical implications: Organizations which intend to invest in TRIZ can obtain a better insight about outcomes and benefits of

implementing TRIZ initiatives. This study will provide those organizations which have already invested in TRIZ with some ideas

to evaluate their maintenance subject qualitatively.

Originality/value: Based on available data, this study is the components of effective selection of maintenance tactics from a new

perspective and according to Altshuller's parameters are identified, extracted and classified in the TRIZ Contradiction matrix.

INTRODUCTION

Rapid advancement in technology, expansion of industrial automation, and increasing the number of machines has led to an ever-

increasing growth in investment on the machinery and physical assets of organizations. Maintenance plays a major role in

reliability, availability, product quality, risk reduction, efficiency enhancement, equipment security, etc. As a result, maintenance

strategy selection is of special importance in industries, particularly considering the need to identify the factors affecting

maintenance strategy selection to use correctly.

Many studies have been conducted about maintenance strategy selection and prioritization based on the effective factors, but no

study has thoroughly sought to identify the components affecting this selection according to Altshuller's parameters (Terninko et

al., 1998) of TRIZ approach.

Zainudeen (2011) conducted a study entitled ―practical applications of decision-making grid‖, in which the grid techniques

considering the frequency of failure and breakdown time have been prioritized(Aslam-Zainudeen and Labib, 2011).


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Alrabghi, & Tiwari (2015) stated that the maintenance system aims to reduce sudden failure and total cost and increase profit and

availability. They also divided the maintenance system into proactive maintenance, corrective maintenance, and condition-based

maintenance as a subcategory of proactive maintenance(Alrabghi and Tiwari, 2015).

Vaneker (2016) qualitatively compared 37 maintenance guidelines with TRIZ principles and then proposed the extracted ideas

and principles as a roadmap for solving the problems in the shortest(Vaneker and van Diepen, 2016).

Trojan and Marcal (2017) conducted a study entitled ―Proposal of Maintenance-types Classification to Clarify Maintenance

Concepts in Production and Operations Management‖, in which they prioritized maintenance concepts in production and

operation management taking into account criteria such as: criticality, intervention modes, planning actions, costs and available

resources using the ELECTRE TRI outranking method. Their study contributed significantly to clarify maintenance concepts

linked to the Production and Operations Management criteria (Trojan and Marçal, 2017).

Seecharan et al. (2018) stated that maintenance management is a vital strategic task given the increasing demand on sustained

availability of machines. They emphasized the need for an approach able to integrate maintenance performance and strategy in

order to adapt existing data on equipment failures and to routinely adjust preventive measures. Hence, maintenance strategies are

incomparable; one strategy should not be applied to all machines, nor all strategies to the same machine. Their findings showed

how the Decision Making Grid (DMG) and Jack-Knife Diagram (JKD) can be incorporated in industrial applications to allocate

appropriate maintenance strategy and track machine performance(Seecharan et al., 2018).

As mentioned above, many studies have identified and prioritized the factors affecting maintenance strategy selection. However,

no study has thoroughly reviewed the literature through meta-synthesis in order to identify and classify the factors affecting

maintenance strategy selection based on Altshuller's parameters in TRIZ contradiction matrix.

The reason for the use of Altshuller's 39 parameters is to compare and identify the factors affecting maintenance strategy selection

comprehensively. Since these parameters are comprehensive enough to be used for identification of the improving and worsening

features in solving all problems, they can be employed as a more general category related to the factors affecting maintenance

strategy selection.

THEORETICAL BACKGROUND

In this section, the related theoretical back grounds have been presented as bellow.

A. Maintenance strategies

Khazraei and Deuse (2011) investigated and compared American, German, Australian, and European maintenance strategies, and

analyzed the strengths and weaknesses of these strategies in terms of structure, implementation, and economic and political issues

as shown in Figure 1. Finally, they proposed a taxonomy of maintenance strategies that included the principles of science and

strategy as the most complete maintenance strategies in 23 classifications (Khazraei and Deuse, 2011). These 23 maintenance

strategies as shown in Figure 2 are as follows: immediate reactive maintenance (IRM), scheduled reactive maintenance (SRM),

deferred reactive maintenance (DRM), operate to failure (OTF), failure-based maintenance (FBM), age-based maintenance

(ABM), block-based maintenance (BBM), constant interval maintenance (CIM), fixed time maintenance (FTM), inspection-based

maintenance (IBM), life-based maintenance (LBM), planned preventive maintenance (PPM), time-based maintenance (TBM),

use-based maintenance (UBM), availability centered maintenance (ACM), business-centered maintenance (BCM), design-out

maintenance (DOM), risk-based maintenance (RBM), reliability-centered maintenance (RCM), total productive maintenance

(TPM), avoidance-based maintenance (ABM), condition-based maintenance (CBM), and detective-based maintenance (DBM).

Fig.1: The initial plan of the system strategy and the environmental factors affecting it [7].


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Going thorough literature on classification of the maintenance strategies, Khazraei and Deuse’s (2011) model is the most

comprehensive study conducted in this area. The diversity of maintenance strategies and the need for their effective selection

involves identifying the components affecting their selection.

B. TRIZ Contradiction matrix

Considering the factors and conditions affecting equipment, today’s competitive environment, and customers’ need for high-

quality and low-cost products, the effective selection of maintenance strategies justifies the need for innovative approaches. So,

higher-level, less costly, and faster scientific activities have been needed in this regard. Recent studies show that TRIZ can

improve the quality and increase the speed of idea generation for development of new products and services by 30-70 (Terninko

et al., 1998).

Many studies have prioritized and selected maintenance strategies based on some effective usual factors such as time, cost, and

risk. But, the present study is different from previous ones due to using of TRIZ contradiction matrix parameters to solve the

contradictions of factors affecting maintenance strategy selection.

Fig.2: A classification of maintenance strategies [7]

As shown in Figure 3, an equipment piece fails and breaks down over time. Hence, there is a need to spend more to keep it in

perfect condition (risk reduction). This shows the concept of contradiction in troubleshooting and machine recovery. Here,

contradiction occurs when two features or states conflict or contradict each other. If there is a contradiction between two features

of a system, making a positive change in one feature (e.g. increasing the quality of a product) would lead to a negative change in

the other (e.g. increased price of the product), thereby failure of the system. TRIZ’s knowledge states that an inventive problem is

accompanied by a contradiction and the problem will be solved when this contradiction is resolved. One of the most important

roles of TRIZ is to identify and analyze contradictions and provide solutions for them (Terninko et al., 1998). Given the fact that

TRIZ's knowledge, proposes innovative and creative solutions for problems based on the concept of contradictions, the present

study recommends the use of this knowledge to solve the contradictions between the factors affecting the appropriate selection of

maintenance strategies.

In the Figure 3, The ―P‖ in a P-F curve refers to potential failure and conversely, the ―F‖ refers to an asset’s functional failure.

C. Meta synthesis

Meta-synthesis was adopted in the present study to compare and analyze qualitative data. Like meta-analysis, meta-synthesis is

used to integrate several studies in order to achieve comprehensive and interpretive findings. Unlike the quantitative meta-

analysis approach which is based on quantitative data and statistical approaches, meta-synthesis focuses on qualitative studies, the

translation of qualitative studies into each other, and the researchers’ deep insight.


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Meta-synthesis is a kind of qualitative study that extracts and reviews information and findings from other related qualitative

studies in order to discover new topics and metaphors by providing a systematic attitude for researchers. Meta-synthesis requires

that researchers conduct a thorough and in-depth review and integrate the findings of relevant qualitative studies. By reviewing

the findings of relevant studies, researchers develop terms that provide a more comprehensive representation of the phenomenon

under study. Like the systematic approach, meta-synthesis presents results larger than the sum of its parts. This study used the

meta-synthesis method proposed by Rousseau and Sandoski (2007) (Sandelowski and Barroso, 2006). This method consists of 7

steps as follows as shown in Figure 4.

1. Development of research questions: The research parameters, including the subject, populations, time constraints, and

method, are developed based on the research questions.

2. Systematic review of texts: The study population consists of all scientific documents, research reports, databases, and

domestic and foreign journals.

3. Search and selection of appropriate papers: The required papers are selected based on parameters such as title, abstract,

content, accessibility, and methodology.

4. Extraction of results: Information of papers is categorized based on the name of authors, year of publication, and

coordination components.

5. Analysis and synthesis of qualitative findings: In this study, all of the factors extracted from the previous studies were

encoded and then the codes with similar concepts were categorized under the same group in order to determine the research

concepts.

6. Control of extracted codes: To this end, Cohen's kappa coefficient (κ) was used to measure inter-rater agreement for

qualitative (categorical) items. Cohen's kappa coefficient ranges between 0 and 1, with values closer to 1 representing higher

inter-rater agreement.

7. Presentation of findings: The findings are presented based on previous studies and extracted codes

Figure 3: P-F curve

Fig.4: The seven steps of meta-synthesis method [8]


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METHODOLOGY

The meta-synthesis steps were fully implemented to identify and extract the factors affecting maintenance strategy selection and

provide a comprehensive model. This process began with the development of questions and finished with the presentation of

findings in this study. After extracting the factors affecting maintenance strategy selection, TRIZ contradiction matrix parameters

corresponding to each of these factors were set as the themes. The research experts included experts of maintenance systems,

managers, and professors of this field. The methodology has been done step by step as bellow.

First step: Development of research questions:

As mentioned above, the first step in meta-synthesis is to develop questions that the researcher aims to answer. The research

questions in the present study were as follows:

- What factors affect maintenance strategy selection?

- What study population was used to identify the factors affecting maintenance strategy selection and what time

constraints were involved?

- How is the framework for modeling the factors affecting maintenance strategy selection?

Second step: Systematic review of texts:

In this study, all papers published from 1960 to 2018 were searched on databases, journals, and search engines using different

keywords. A total of 534 papers were found in this step. The related information have been shown in the following tables.

Table 1. The Search resources

Table 2. Reviewed journals

Table 3. Words searched

Third step: Search and selection of appropriate papers

To select appropriate papers based on the algorithm shown in Figure 5, various parameters such as title, abstract, content,

accessibility, and methodology were evaluated.

Sources Row Sources Row

Springer 3 Science Direct(Elsevier) 1

Emerald 4 IEE 2

Reviewed journals Row Reviewed journals Row

Loss Prevention in the Process Industries 11 Quality in Maintenance Engineering 1

Hazardous Materials 12 Industrial Management 2

Modern Processes in Manufacturing and Production 13 Production Economics 3

Computational Design and Engineering 14 Reliability Engineering and System Safety 4

Process Mechanical Engineering 15 Operational Research 5

Advanced Manufacturing Technology 16 Intelligent Manufacturing 6

Engineering Applications of Artificial Intelligence 17 Production Research 7

Statistical Planning and Inference 18 Computer Integrated Manufacturing 8

the Operations Research Society of Japan 19 Modeling, Simulation, and Scientific Computing 9

Operations Management 10

Words searched Row Words searched Row

Opportunistic Maintenance Modeling 8 Preventive Maintenance Strategy 1

Preventive Maintenance Policy 9 Maintenance Policy 2

Maintenance Policy Assessment 10 Maintenance Management System 3

Maintainability Evaluation Model 11 Scheduling Maintenance Activity 4

Predictive Maintenance Policy System 12 Repair and Overhaul (MRO) Strategies 5

Maintenance Optimization Model 13 Reliability 6

Condition-Based Maintenance Systems 7


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Number of found resources 534

Number of abstract reviewed 414

Number to review full content 325

Number of articles to evaluate the research method

247

Total final articles 210

Rejected articles (title) 116

Rejected articles (Abstract) 93

Rejected articles (content) 78

Rejected articles (methodology) 37

Fig.5: The algorithms of final selection.

Fourth step: Extraction of results:

Information of papers was categorized based on the name of authors, year of publication, and coordination components.

Fifth step: Analysis and synthesis of qualitative findings:

At first, all factors extracted from previous studies were encoded and then the codes with the similar concept were categorized

under the same group, according to Altshuller's parameters, in order to determine the research concepts. For example, ―machine

complexity‖ and ―number of machine components‖, which were discussed in previous studies, were selected as two codes and

then were categorized as ―machine complexity‖. It is noteworthy that theme categorization was based on TRIZ contradiction

matrix parameters.

A total of 26 concepts and 59 codes were extracted as the factors affecting maintenance strategy selection following the content

analysis of 210 selected papers. Table 4 shows the extracted code corresponding to each category and concept.


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Table 4. Extracted Codes


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Sixth step: Control of extracted codes:

To control the extracted concepts, two experts of maintenance were asked to rate them as shown in Table 5. The inter-rater

agreement was measured using Cohen's kappa coefficient as shown in Table 6. This index is used to measure variables with the

same measurement level and equal number of categories. Cohen's kappa coefficient ranges between 0 and 1, and values closer to

1 represent higher inter-rater agreement. Since the level of significance was smaller than 0.05, it is concluded that the error of

extracted codes is rejected and the extracted codes are of acceptable reliability.

Table 5. Experts' answer

Total Diagnostician 2

1 0

9 9 0 0 Diagnostician 1

64 63 1 1

73 72 1 Total

Table 6. Cohen's kappa coefficient

Statistically significant Amount

0.02695 0.83 Cohen's kappa coefficient

73 Diagnostician


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Seventh step: Findings presentation:

Content analysis is a stage of information process through which the communication content changes into summarized and

comparable data through a set of classified and systematic rules. Shannon entropy is a powerful tool for data processing in content

analysis. In information theory, entropy is an indicator used to measure uncertainty through the probability distribution. There are

several methods for determining the weight of indices, one of which is Shannon entropy, where messages are counted in terms of

the number of categories for each respondent and then the degree of importance of each category is calculated based on its

information load. Shannon entropy was used in the present study due to its strength and ease of calculation.

The coefficients obtained as seen in Table 7 show that the highest coefficient of importance was related to energy consumption,

energy consumption rate, energy waste, waiting times, inefficiency time, down time, idle time, and guarantee period. Hence, it

can be stated that the above-mentioned factors are the most effective ones in maintenance strategy selection.

Table 7. Ranking of extracted code by Shannon entropy


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CONCLUSION

As previously mentioned, maintenance strategy selection is very important in industries, particularly due to the need to identify

the factors affecting maintenance strategy selection and use correctly. Many studies have been conducted about the selection and

prioritization of maintenance strategies based on the factors affecting them using methods such as MCDM, the ant colony

optimization algorithm, and DMG matrix. However, no study has sought to identify the components affecting this selection and

prioritization. In order to identify the factors affecting maintenance strategy selection, it was necessary to first identify the most

comprehensive classification of these strategies. The present study used the strategies proposed by Khazraei and Deuse (2011) as

the most comprehensive classification of maintenance strategy. Then, the factors affecting maintenance strategy selection were

identified based on Altshuller's parameters in TRIZ contradiction matrix and systematically categorized through meta-synthesis.

To this end, a total of 534 papers were reviewed and 210 papers were selected for meta-synthesis. The codes were extracted from

selected papers and compared with Altshuller's parameters. After the factors affecting maintenance strategy selection were

identified, they were classified into 26 concepts and 59 codes, and prioritized using Shannon entropy. Accordingly, the codes

were prioritized in 13 levels based on the results. Time, energy and reliability were among the factors assigned to Level 1 in the

prioritization. The reason for the selection of TRIZ contradiction matrix parameters and their comparison with the factors

affecting maintenance strategy selection was their comprehensiveness. One of the advantages of the present study over previous

ones was its review of all of the papers published on maintenance and identification, extraction, and prioritization of the factors

affecting maintenance strategy selection based on Altshuller's parameters. One of its innovations was the comparison of the

factors affecting maintenance strategy selection with Altshuller's 39 parameters using meta-synthesis. As a result, the

characteristic feature of Altshuller's 39 parameters in solving the contradictions of problems was added to the classification of the

factors affecting maintenance strategy selection.

The study findings can help managers and maintenance experts to eliminate the contradictions between the factors affecting

maintenance strategy selection and select appropriate strategies in the shortest time possible. One of the applied recommendations

for future studies is the use of meta-synthesis to find out the relationship between maintenance strategies and the 40 principles of

TRIZ based on predictive, proactive, predetermined, prospective, and corrective policies. In addition, it is recommended to

develop the TRIZ contradiction matrix and solve contradictions between maintenance strategies using the effective factors.

Another recommendation for future studies is to analyze malfunctioned machines using meta-synthesis and develop appropriate

scenarios of maintenance for each machine based on its function in order to facilitate the decision-making process.

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