Quality Improvements Towards Zero Defects : Addressing the Implementation Gap Between Industry and Literature

PAPER WITHIN Production Systems

AUTHOR: Gabriella Gustafsson & Wiktoria Rydin JÖNKÖPING June 2020

Quality Improvements

Towards Zero Defects

Addressing the Implementation Gap Between

Industry and Literature

subject area Production System with a specialization in production development and management. The work is a part of the Master of Science program. The authors take full responsibility for opinions, conclusions and findings presented.

Examiner: Carin Rösiö

Supervisor: Gary Linnéusson

Scope: 30 credits (second cycle)

I

Abstract

Customers today demand products of high quality, and industries must cope with issues related to that to stay competitive. Therefore, an endeavor to achieve zero defects and to work with zero defect manufacturing (ZDM) is common in industries today. ZDM aims to reduce the number of failures within a manufacturing process and thus only producing faultless products. Since defected items result in unexpected work, extra costs, claims and unsatisfied customers, it is important to avoid that in order to secure the company’s market share. Even though it implies challenges, companies must work with ZDM and quality tools to stay competitive. However, there is a gap between the literature of ZDM and how to accomplish ZDM in practice, which makes it hard for companies to apply the method. Hence, this thesis aims to address this gap and present how the human factors and quality contribute to the goal of zero defects.

When working with a manually driven manufacturing setting, human factors must be considered as an important aspect. Mistakes will occur as long as humans work with the products, but the prerequisites for doing right must be as good as possible to be able to decrease the number of mistakes. Another factor to consider is the internal quality of different processes to ensure that customer demands are achieved through all stages. This study focused on finding suggestions for improvements towards zero defects in manual assembly and to present general improvement actions. The thesis is based on three main fields: ZDM, quality and human factors. The findings are connected both to literature searches made within these fields, but also through a case study at the focal company. In the analysis chapter, the reader is provided with information about how the specified problem areas are linked together and to the three main fields. By combining the literature search with a case study at a focal company, findings could be detected, collected and analyzed.

Four areas could be identified in the analysis and highlighted in the discussion of the research questions. The highlighted areas were further used as a foundation to establish suggestion within the important areas. These acts as practical guidelines for how to reach zero defects in an existing production with the goal of minimizing the implementation gap of ZDM.

Keywords

II

Acknowledgment

We would like to start by expressing our gratitude to the people who have helped us along the way. First, we would like to thank our supervisor Gary Linnéusson at School of Engineering in Jönköping, for guidance and support throughout the project. Moreover, we would like to thank the focal company for the opportunity to belong to their project and be provided with information and inestimable inputs. A special thanks to Nina Ström, our supervisor at the focal company, for all help and support.

III

Contents

1

Introduction ... 1

1.1 BACKGROUND ... 1

1.2 PROBLEM DESCRIPTION ... 2

1.3 PURPOSE AND RESEARCH QUESTIONS ... 3

1.4 DELIMITATIONS ... 3

1.5 OUTLINE ... 3

2

Theoretical Background ... 5

2.1 ZERO DEFECTS ... 5

2.2 QUALITY ... 6

2.2.1 Total Quality Management ... 7

2.2.2 Supplier Quality ... 7

2.2.3 Internal Quality Assurance ... 8

2.2.4 FMEA ... 8

2.3 HUMAN FACTORS ENGINEERING ... 11

2.3.1 Human Error ... 12

2.3.2 Situation Awareness ... 14

2.3.3 Acknowledgment and Responsibility ... 16

2.3.4 Factors Affecting Human Performance ... 16

3

Method and Implementation ... 18

3.1 RESEARCH APPROACH ... 18

3.1.1 Link Between Methods and Research Questions ... 18

3.2 LITERATURE REVIEW ... 19

3.3 CASE STUDY ... 21

3.3.1 Case Company ... 22

3.4 DATA COLLECTION ... 22

3.4.1 Disruption Poll ... 23

IV

3.4.3 Survey Assembly Instruction ... 23

3.4.4 Documentation of Observation Data ... 24

3.4.5 Documentation of Claim Data ... 24

3.4.6 Competence Assessment ... 24 3.5 IMPLEMENTATION ... 25 3.5.1 Fishbone Diagram ... 25 3.5.2 5 Why Analysis ... 25 3.5.3 FMEA ... 26 3.6 ETHICAL CONSIDERATION ... 26

3.7 VALIDITY AND RELIABILITY ... 27

4

Findings and Analysis ... 28

4.1 LITERATURE REVIEW ... 28

4.2 CASE STUDY ... 29

4.2.1 Introduction for new employees ... 29

4.2.2 Disruption Poll ... 29

4.2.3 Instruction Failure Poll ... 30

4.2.4 Survey Assembly Instruction ... 30

4.2.5 Documentation of Observation Data ... 31

4.2.6 Documentation of Claim Data ... 31

4.2.7 Competence Assessment ... 32

4.2.8 Summary of Case Study Findings ... 32

4.3 IMPLEMENTATION ... 33 4.3.1 Fishbone Diagrams ... 33 4.3.2 5 Why Analysis ... 34 4.3.3 FMEA ... 35 4.3.4 Summary of Implementation ... 35 4.4 ANALYSIS ... 36

5

Discussion and Conclusion ... 39

5.1 DISCUSSION OF METHOD ... 39

V

5.3 DISCUSSION OF FINDINGS ... 40

5.4 CONCLUSIONS ... 45

6

References ... 47

7

Appendices ... 51

7.1 APPENDIX 1–DISRUPTION POLL AND RESULT ... 51

7.2 APPENDIX 2–INSTRUCTION FAILURE POLL ... 53

7.3 APPENDIX 3–SURVEY ASSEMBLY INSTRUCTION ... 54

7.4 APPENDIX 4–OBSERVATION DATA ... 57

7.5 APPENDIX 5–CLAIM DATA ... 58

7.6 APPENDIX 6–COMPETENCE ASSESSMENT ... 59

7.7 APPENDIX 7–FISHBONE DIAGRAM ... 60

7.8 APPENDIX 8–5WHY ANALYSIS ... 62

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1

Introduction

This section will present a background to the problem of this study. Furthermore, a problem description, purpose and the study’s research questions will be presented in this chapter. Finally, the delimitations and the outline are stated.

1.1

To meet the customers' demands in the industry today, high quality is needed (Chahar, Hatwal, & Sen, 2019). If a product fails to keep what it promises, the customer is likely to complain. In today’s society with easy access to social media, it can have enormous consequences, for example loss of customers. Therefore, it is of great importance for the manufacturing companies to ensure the quality of the products and to have as few defected items as possible, maybe more important now than ever. A company that succeeds in having high-quality products is more likely to keep its customers and to be recommended for others and, in that way, attract new customers (Patel S. , 2016). To ensure high quality products within a company and increase the competitiveness of the company, several different aspects must be taken into consideration (Gewohn, Usländer, & Beyerer, 2018). One aspect to consider is the initial raw material used for the products, which must be of high quality in order for the finished product to have the possibility to meet the demands. Moreover, the workforce must have high skills and be supported by experts when needed (Chahar, Hatwal, & Sen, 2019; Dreyfus & Kyritsis, 2018). Further, there needs to be an established knowledge and understanding within the company of how the products fit into the market and how they will be used (Gewohn, Usländer, & Beyerer, 2018).

Companies that successfully meet the customers’ need and expectations of the products’ quality by working in a systematically and innovatively way, often gains competitive advantage compared to companies that do not do that (Bergman & Klefsjö, 2007). Quality management can be found as early as during World War II in The United States when so-called quality gurus revolutionized the attitude towards quality by highlighting its significance (Patel S. , 2016). Moreover, in 1970, Japanese companies got a huge competitive advantage in the industrial market by improving their industries according to the customers’ requirements and expectations. The effects of these changes caused some industries in the USA into bankruptcy, due to changes in the market’s expectations (Bergman & Klefsjö, 2007). All this by moving the focus to the customers’ requirements and expectations (Bergman & Klefsjö, 2007). Similar, according to Patel (2016), quality improvements were included in the manufacturing process in the early twentieth century. Regardless of the long involvement of quality in the manufacturing industries, challenges of how to manage quality optimizations still exist.

The quality of a product is not only affected by what happens inhouse, but is also greatly dependent on a company’s suppliers and their contribution and knowledge about quality (Noshada & Awasthib, 2015). Moreover, the technical tools must maintain durability and high quality to create faultless products (Fakert, Gromov, Muller, Polzer, & Wolf, 2008). Further, continuous improvements in machinability and more advanced

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technical tools are desirable factors that contribute to the quality of the products (Fakert, Gromov, Muller, Polzer, & Wolf, 2008). Another fundamental aspect to consider in manual production, when speaking about quality, is the human effect on the different operations (Ostadi & Masouleh. S, 2019). As long as the assembly is driven by humans, errors and defects will occur and cannot be entirely avoided (Wickens & Hollands, 1999; Guastello, 2013). However, several things can be done to prevent errors caused by humans, for example by making clear guidelines and by using correct tools effectively, the number of errors and defected products can be minimized. Today there are various established methods available to analyze, improve and confirm the quality of a company, for example failure mode and effect analysis (Xiuxu & Yuming, 2010), fishbone diagram (Tongyuan, Chao, & Lixiang, 2018) and zero defect manufacturing (Eger, et al., 2018), depending on the desired outcome. Examples of desired outcomes could be minimizing waste, minimize defected items or decrease the number of customer claims.

Customer claims result in unexpected work, extra costs and unsatisfied customers, which companies want to avoid. Therefore, zero defects and zero defect manufacturing (ZDM) are important strategies to be able to prevent and predict scrapped parts and failures in the production system (Eger, et al., 2018). ZDM is an efficient strategy when striving for zero defected items (Psarommatis, May, Dreyfus, & Kiritsis, 2019). To achieve zero defects in a manual production may seem impossible, but there should be an endeavor towards perfection within the quality of both products and processes (Psarommatis & Kiritsis, 2018). The situation at the companies has changed over time and with new technologies, such as computer-based data storage, the zero defect manufacturing (ZDM) has been enabled (Psarommatis, May, Dreyfus, & Kiritsis, 2019). ZDM is a strategy that aims to reduce and mitigate failures within the manufacturing process and the goal is to remove defected items in production (Psarommatis, May, Dreyfus, & Kiritsis, 2019; Dreyfus & Kyritsis, 2018; Eger, et al., 2018). For a company to be more environmentally friendly and to maintain an effective assembly with zero defects, the standard of ZDM is the way to go (Psarommatis, May, Dreyfus, & Kiritsis, 2019).

1.2

Due to challenges in quality assurance that companies face today, an interest in finding efficient ways towards increasing and maintaining high quality is essential. There are many areas affecting the work to gain and maintain the quality the customer asks for, such as controls and human factors (Malega, 2016). Thus, several different aspects must be considered, evaluated, and identified in order for the company to know how to stay competitive and develop end-product quality (Zhu, Alard, & P, 2007).

A potential implementation gap was identified between the theories about how to accomplish ZDM, resulting in no claims, and how to manage that in an assembly in practice. Even though the theory present solutions and guidelines applicable for companies, it was sometimes difficult to implement them due to a lack of generalizable instructions. Thus, this project aims to identify how the gap can be supported by

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collecting empirical data from a case company and shows how the literature can support the journey towards zero defects. Also, how these areas could be improved to be able to meet the target of zero defected items in a general assembly.

1.3

The project aimed to address the identified gap between the literature and the ZDM implementation in an assembly in practice by identifying key factors that affects the output and the work towards zero defects. Therefore, the research questions were:

1. Which problem areas can be specified within the goal of zero defects in the assembly?

2. Which of the specified problem areas can be identified to have the most effect of the goal of zero defects?

3. How can the specified problem areas be supported by the suggested improvements?

1.4

This project was limited to one case containing one company in which one cell and one line was examined. When collecting data, other cells and lines at the focal company were not taken into consideration. Covering the entire assembly would have required much work and this was not possible to include within the timeframe of this project. Therefore, the case findings were restricted to focus on one cell and one line to get a realistic and informative result which can be applied to the other assembly units. Even though the case focused on two different assembly units, i.e. one cell and one line, the information will be combined to one analysis, to simplify the result and discussion. Since the goal of zero defects is rather extensive and involves many different areas and aspects, the focus of the study was limited to the research fields of ZDM, quality and human factors. Thus, areas like for example financial aspects, choice of production systems and external factors is not considered.

1.5

The thesis is based on five main chapters with several contributing subheadings. In chapter one, an introduction of the subject and background are presented to provide the readers with the positioning of the study as well as the identified knowledge gap. Moreover, the study’s research questions are presented together with the purpose and delimitations. The second chapter, theoretical background, begins with a literature review including a pre-study, presenting relevant theories to further encircle the scope of the study. The pre-study is then followed by a more detailed literature search of the scope in order to support the discussion and conclusion of the research questions and build a foundation for the case study. The third chapter, the method and implementation chapter, describes and presents motivations to the structure of the theoretical background and how it was conducted. Furthermore, the overall approach of the study is explained, and a guide of the order to which the research questions are supposed to be answered. Further this chapter also motivates and describes the implemented

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methods used to analyze and collect data of the conducted case. The method chapter is then followed by the findings from the project, i.e. the fourth chapter, where the linked analysis related to the findings also are presented. In the fifth chapter a summary and a discussion of the gathered data, method and result will be presented as well as a discussion regarding the realistic effects of this study. Other relevant information can be found in the appendices.

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2

Theoretical Background

This chapter presents relevant theories and methods needed to understand as well as to establish a foundation for the project. The main focus areas are zero defect manufacturing, quality and human factors, which then are divided into subheadings for a clearer understanding.

2.1

Zero defect manufacturing (ZDM) is an efficient strategy towards an assembly that delivers zero items with defects (Eger, et al., 2018; Psarommatis, May, Dreyfus, & Kiritsis, 2019). The purpose of ZDM is to reduce the number of errors and faults in the manufacturing process which in turn will result in a more cost-efficient, environmentally friendly and competitive production process (Psarommatis & Kiritsis, 2018). As a result of the improved manufacturing process, ZDM is also related to other benefits, for example less scraped output, faster lead times and deliveries, resilience towards problems, increased planning abilities and confidence in availability and output quality (Lindström, et al., 2019). Similarly, Bai & Zhang (2018) highlights several advantages of ZDM, and the concept’s contribution towards a significant reduction of the costs of the company’s defective products. The concept contains four elements: detect, predict, repair and prevent and they can be seen in Figure 1 (Psarommatis & Kiritsis, 2018). Psarommatis et al. (2019) further describe it as if the defects are detected they can be repaired and the data collected by the defect detection can be used for prediction of failures and to prevent them. Though it seems impossible to achieve zero defects in manual production, the concept strives towards perfection intending to improve the quality of products and processes (Psarommatis & Kiritsis, 2018).

Figure 1 Zero defect manufacturing elements, adapted from Psarommatis et al. (2019) The literature field pertained to ZDM is extensive, and there are many areas and strategies linked to the fundamental ideas of process improvements of ZDM (Lindström, et al., 2019). Furthermore, there is an alignment between the benefits of the ZDM strategy and the ideal industry 4.0 strategy, and thus ZDM can be considered

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as a contribution towards an integrated knowledge flow. The flow is established through a combination of different information from multiple systems (Lindström, et al., 2019). One aspect of the theory related to zero defect production (ZDP) or ZDM is a theory by Mycklebust (2013). He presents a lifecycle approach of ZDM to highlight the importance of a combined model, including product quality, resource performance, product-plant view and lifecycle analysis. That results in a model consisting of an extensive knowledge-feedback loop and a collection of real-time data. Moreover, Ostadi & Masouleh (2019) discuss the errors causing the defects in a manual production plant and link them to both human, technology and process-related errors using a failure mode and effect analysis (FMEA). Based on the result from the FMEA, Ostadi & Masouleh (2019) states that the main factor to consider in the work towards ZDP is the human factors, i.e. aspects as stress and lack of motivation. Furthermore, Dreyfus & Kyritsis (2018) describes the importance of monitoring and understanding the humans’ role in the production to maintain the high quality. Moreover, Ferretti, Caputo, Penza & D'Addona (2013) present another action strategy towards ZDP and ZDM constituting of indirect actions, i.e. training of operators, raw material inspection, internal controls and maintenance and direct actions, such as process monitoring.

In summary, different factors contribute to zero defect manufacturing and the theory presents strategies for companies to follow. The problem is the gap that occurs between the theories and the company’s implementation of it. Here the theories present guidelines for how to accomplish ZDM, but they are not always easy for the company to follow. However, it can be said that several different factors contribute to zero defect manufacturing, in which there are two central aspects to the concept linking theories together: quality and human factors. These factors will, therefore, be further described in the following chapters.

2.2

Better quality contributes to the success and profitability of a business (Bergman & Klefsjö, 2007). With high quality comes more satisfied customers that are more likely to return and buy the products again, and also recommend them to others (Bergman & Klefsjö, 2007). The emphasis on sustainable production is increasing, and to be able to meet the customer’s demands, it is of great importance to use the resources efficiently (Colledaniab, et al., 2014). Also, to be efficient along the life cycle of the process, product and production is important (Colledaniab, et al., 2014). A strong interaction between quality, production planning and maintenance can be seen and also their relation to so-called production quality, which is described by Colledaniab et al. (2014, p. 773) as “the company's ability to timely deliver the desired quantities of products

that are conforming to the customer expectations, while keeping resource utilization to a minimum level”. Still, it is important to remember that quality is a broad expression

7 2.2.1 Total Quality Management

Total quality management (TQM) is described by Bergman & Klefsjö (2007) as a constant endeavor to fulfill and hopefully exceed the customer’s needs at the lowest cost. To continuously work with improvements and that all involved should be committed are also important. It is an ongoing process of satisfying the needs of the customers and a vital part in generating business profit (Chaudary, Zafar, & Salman, 2015). TQM is built by several management tools and methods which all focus on fulfilling the demands of customers (York & Miree, 2004). This is done by identifying their spoken and unspoken needs, be responsive to the changing market and ensuring the improvement of efficiency in the process that produces products or services (York & Miree, 2004). Supporters of TQM also indicate that an implementation of TQM will have a positive result on the company’s financial performance (York & Miree, 2004). However, a successful implementation and ongoing process of TQM is based on the commitment of all employees and their contribution to continuous improvements and willingness to combat shrink costs and waste (Chaudary, Zafar, & Salman, 2015). All TQM principles are shown in Figure 2.

Figure 2 TQM principles, adapted from Bergman & Klefsjö (2007) 2.2.2 Supplier Quality

Maintaining and developing the quality of suppliers are important activities for several different reasons (Noshada & Awasthib, 2015). High quality contributes to lower claim costs and if the claims are low, the customers are more pleased with the products and are more likely to recommend the company to others (Noshada & Awasthib, 2015). One way of ensuring the supplier quality is to use supplier auditing as a tool for quality management (Zulkifli, Abd. Aziz, & Sivalingam, 2015). By a systematic and independent process, evidence for the fulfillment of principles, compliances, green programs and agreed standards can be determined (Zulkifli, Abd. Aziz, & Sivalingam, 2015). As the need for different products changes over time, the sustained quality needs to be assured to keep the end-user satisfied and remain at the market (Walker & Hon, 1988). Another factor described by Malega (2016) as one of the most important key factors to stay competitive is the supplier quality assurance. The supplier quality assurance must not conflict with the company strategies and the company must be

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confident that their supplier delivers what the customer demand in a satisfying way (Malega, 2016). It is further described by Walker & Hon (1988) that supplier quality improvements, which are connected to the supplier quality assurance, are based on three elements: customer commitment, documentation of requirements and introduction of the supplier quality improvements to the suppliers. These elements depend on several factors that differ among different companies and every relationship needs its specialized way (Walker & Hon, 1988).

2.2.3 Internal Quality Assurance

At the same time as the quality assurance among suppliers is important, it is also of great importance to ensure the quality within the company. To continuously work with internal quality assurance can be seen as one central factor in order to be successful (Lundgren, Hedlind, & Kjellberg, 2015). Internal quality is connected both to the people and to the group and one must take responsibility in order to succeed (Andriansyaha, Taufiqurokhmana, & Suardi Wekkeb, 2019). When a company deals with humans and not only robot procedures, an understanding of structures and basic morals are vital and contribute to the process of learning how to implement the quality into the work process (Andriansyaha, Taufiqurokhmana, & Suardi Wekkeb, 2019). To ensure the correct product quality, every process and operation must be designed in the best possible way. A more holistic perspective of the quality assurance is needed where it is included as an integrated part of the whole product realization process (Lundgren, Hedlind, & Kjellberg, 2015). Lundgren et al. (2015) further explain the application of a front-loading approach, i.e. most of the work effort is assigned to the planning stage to ensure a careful planning process. It also ensures that problems are detected in an early stage and can be prevented before they occur.

2.2.4 FMEA

FMEA stands for failure mode and effect analysis and is a tool within TQM that helps to identify potential failures before it happens (Bergman & Klefsjö, 2007; Xiuxu & Yuming, 2010). It is one of several quality control methods and contains actions to minimize the failure risks within a production system (Burduk & Krenczyk, 2017). The method is used as a systematic review of products, or processes, function, errors, causes and consequences (Bergman & Klefsjö, 2007). Xiuxu & Yuming (2010) describe FMEA as a vital part of a company’s assurance of quality improvement of products and effectivity in manufacturing. The practical application of FMEA is of two different types; product FMEA and process FMEA, and the comparison them between are showed in Table 1 (Kania, Cesarz-Andraczke, & Odrobinski, 2018).

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Table 1 Comparison of product and process FMEA, adapted from Kania et al. (2018)

Product FMEA Process FMEA Criterion of analysis Fulfillment of utility functions by

the product

Correct process realization, fulfillment of process

requirements

Subject of analysis Product, subassemblies, elements

Stage of the process (operations, actions,

procedures)

Asked questions What causes may lead to total or partial disappearance of the

product’s function? What consequences may be associated with them?

What defects may occur in a given stage of the process and

what may be their impact on the product/construction or

service defects

Examples of defects Element cracking, no medium flow

Wrong connection, breaking time, misadvising

Examples of defected causes

Construction defects, wear, service errors, environmental

impact

Machinery/device errors, man mistakes, incorrect methods,

incorrect material, incompetence, improper work

organization

Examples of effects Failure/loss of function, medical hazard/danger to life

Nonconformities, lower performance, high cost, too

long waiting time

Kania et al. (2018) describes two approaches of FMEA that are considered: problems and systematic. Problems are areas where all detected problems are analyzed and activities are selected based on the problem, previous experience, failure analysis, etc. Systematic is an approach where the analysis of the products or processes is made broadly as a system. The first step is to decide the boundaries of the system, and then to identify the subsystems. It is a more generalized approach than the problem approach and it makes the analysis more transparent.

The first step of an FMEA analysis is to point out the operations in a process (Malega, 2016). The next step is the identification process of possible defects, followed by a determination of the effects caused by their occurrence and then the possible causes are found (Malega, 2016). These steps can be seen in Figure 3.

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Figure 3 FMEA activity model, adapted from Malega (2016)

When performing an FMEA, pre-defined parameter symbols are used, as shown in Table 2 below, and they represent the numerical values of the terms and are calculated according to the formula given (Burduk & Krenczyk, 2017). Usually the range of 1-7 or 1-10 is used to make the assessment, but it can differ depending on what the analyzing team decides (Burduk & Krenczyk, 2017; Kania, Cesarz-Andraczke, & Odrobinski, 2018; Xiuxu & Yuming, 2010; Valdes, 2015).

Table 2 Characteristics of the parameters, adapted from Burduk & Krenczyk (2017)

Parameter symbol Parameter name Description

S Severity Whose value is the level of damage effects that occurs

in the system O Occurrence The value which represents

the frequency of failure D Detectability The ability to detect a

potential failure

RPN = S * O * D

If the range of 1-10 is used, the value of the risk priority number (RPN) will be somewhere between 1-1000 and a high number of RPN shows a high risk in the process (Burduk & Krenczyk, 2017). If step 3, 4 or 5 from Figure 3 result in high numbers, it means high severity, high probability of occurrence and low probability of discovering the most prioritized failure which has the most serious effect (Malega, 2016).

How to assess the severity, occurrence and detectability are described in Table 3, Table 4 and Table 5 (Brassard, Finn, Ritter, & Ginn, 2003). It shows how to analyze the different values based on how much impact it has. When the assessment is finalized and each process has got a value of severity, occurrence and detectability, these three numbers are multiplied and results in an RPN number. The process with the highest RPN number is identified as the highest risk. The full FMEA form used for doing the FMEA is shown in appendix 7.1.

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Table 3 Severity assessment, based on Brassard et al. (2003)

Severity (S)

Criteria Value

The user will probably not detect the problem 1 Minor impact, the user will notice it as a minor disturbance 2-3 Noticeable impact, e.g. annoying noise or a minor function

decrease 4-6 Significant inconvenience which need reparation 7-8 High severity, risk for personal injury or violation of law 9-10

Table 4 Occurrence assessment, based on Brassard et al. (2003)

Occurrence (O) Criteria Value Remote possibility 1 Low probability 2-3 Moderate probability 4-6 High probability 7-8 Very high probability 9-10

Table 5 Detectability assessment, based on Brassard et al. (2003)

Detectability (D)

Criteria Value

Very low probability that the defect reaches the customer 1 Low risk that the defect reaches the customer 2-3 Moderate risk that the defect reaches the customer 4-6 High risk that the defect reaches the customer 7-8 Very high risk that the defect reaches the customer 9-10

A potential risk with FMEA is that it will not be utilized to its full potential in the manufacturing process (Xiuxu & Yuming, 2010). This problem often occurs due to a lack of relevant and effective management and when a standard for the FMEA knowledge structure is missing (Xiuxu & Yuming, 2010).

2.3

Human factor is a familiar concept that can be traced back to prehistorical times when one first made tools to enhance the capability of performing different tasks in everyday life (Guastello, 2013). Since then, the concept of human factors has evolved and has been transformed into the practice today known as human factors engineering (HFE). The main goal of HFE is to reduce errors, increase productivity and enhance comfort and combability of humans while interacting with a system (Wickens & Hollands, 1999). Another more recent definition of HFE, which has been adopted by this study, is highlighted by Grosse, Calzavara, Glock & Sgarbossa (2017, p. 6901), as “the

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scientific discipline concerned with the understanding of interactions among humans and other elements of a system, and the profession that applies theory, principles, data and methods to design in order to optimize human well-being and overall system performance”.

Furthermore, it is known that each human has their unique background, which affects their behavior and abilities, not only in their private life but also in the workplace (Wickens & Hollands, 1999). Thus, it becomes important to consider HFE while discussing the quality of products which at some point has been in contact with or developed by humans. Therefore, this chapter will present theories and practices within HFE, which is relevant in order to understand how the different factors in HFE affect the quality and performance of a company.

2.3.1 Human Error

When analyzing the performance and quality of a production system or an individual machine, it is necessary to understand the different factors that can affect the outcome. Since human-computer interfaces and human-production units still are active in the industry today, there is a need to consider human error as a factor when analyzing the performance of a system. (Guastello, 2013)

Human error is generally divided into five different sub-categories, whereas three of them are related to the personal decision-making and action based on previous knowledge and surrounding information, while the other two categories are related to the timing and order (Guastello, 2013).

Table 6 presents an overview of the categories and presents an action example for each error.

Table 6 Type of error, adapted from Guastello (2013)

Type of error Definition Example

Commission

When operators have the right intention but choose the wrong actions

Pushes the wrong button

Omission When operators fail to perform the

needed action

Forgetting to include or attach parts in an assembly

Extraneous acts

When operators perform unrelated, unnecessary or unconnected actions.

Fixing something that isn’t broken

Sequential Actions performed in the wrong

order.

Attaching part B before part A, when the order should be A and then B.

Timing Actions performed too soon or too

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Similar to the general categories of errors, there is another classification of human errors which is linked to a behavior model separating human errors into three categories which are skill-, rule- and knowledge-based errors (SRK) (Marquardt, 2019). These levels are more detailed described by Cummings (2018) whereas she states that skill-based behavior is defined by highly automatic and sensory-motor actions that have been acquired by the operator through training and repetition. Furthermore, the next level of the model is the rule-based behavior which contains the actions supported by underlaying subroutines, rules and procedures. Finally, the third level, with the highest level of cognition in the model is the knowledge-based actions, where mental models are used by the operators to guide and aid the actions performed. The actions are performed through a deep understanding of the identified problem and previously gained knowledge about the specific task.

According to another classification scheme of the human error process, presented in Figure 4 and developed by Wickens and Hollands (1999), the errors are divided into five categories which are linked to three levels of stimulus evidence. Thus, the scheme presents an information processing approach to how humans receive and process information and selects an appropriate action (Wickens & Hollands, 1999).

Figure 4 Classification scheme of Human Errors, adapted from Wickens & Hollands (1999)

Moreover, Wickens and Hollands (1999) classify the errors in the scheme as follows: mistakes, which are separated in knowledge-based mistakes and rule-based mistakes, slips, lapses and mode errors. The areas are further described in Table 7 presented below.

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Table 7 Error classifications, adapted from Wickens and Hollands (1999)

Classifications Definition & Process

Example of Shortcomings Mistakes

Knowledge-based

Incorrect knowledge i.e. wrongly formulated intentions resulting in wrongly intended action

• Failure to interpret the information, displays and communications

• Insufficient knowledge or expertise

Rule-based Applied rules are wrong i.e. wrongly formulated

intentions resulting in wrongly applied rules intended action is wrong (if-then)

• Misinterpretation of the situation and surroundings, which lead to misapplied rules. • “Bad rules” is learned and applied

Slips Intended action is correct but incorrectly carried out

• When the right intentions are exchanged for a well-practiced behavior pattern.

• Failure to note small changes in work process

• Failure to monitor relatively automated action sequences

Laps Failing to carry out actions at all

• Memory problem, Forgetfulness

Mode errors Appropriate actions/modes for one operation is applied in the wrong scenario

• Failure situation awareness and understanding of the problem

2.3.2 Situation Awareness

To further understand the underlying and direct shortcomings resulting in human errors, one factor to consider is situation awareness (SA), which conceptualizes the person’s understanding and integration of the surroundings (Marquardt, 2019). SA has been defined by Endsley (1995, p. 36), as a human’s “perception of the elements in the

environment within a volume of time and space, the comprehension of their meaning, and the projection of their status in the near future”.

Endsley (1995) separates SA into three different levels, where the first level is the operator’s perception of surrounding elements, the next level is the comprehension of the situation and the third and final level is the ability of prediction for the future situation. Furthermore, Endsley (2015) describes the relationship between the levels as ascending and not linear stages, which implies that the levels are not necessarily data-driven. Thus can a person for example use the current understanding and projections of a process, level 2 and 3, to generate assumptions regarding level 1 information, both rightly and wrongly (Endsley, 2015). A person who understands the current situation

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has higher SA than a person who has accessibility to all data, but does not understand its meaning (Endsley, 2015).

Figure 5 displays the schematic view of a person’s dynamic decision making, where SA is presented as a vital part of the system. The figure also presents the importance of individual experience, cognitive abilities, mental state, environment and complexity of the work task.

Figure 5 Schematic figure of dynamic decision-making including SA, modified from Endsley (1995)

The model by Endsley (1995) highlights how the experience, training and abilities supports both the SA and the following decision-making process of a person. Strater & Bolstad (2008) present three conditions needed for a successful SA development for people, which is feedback, repetitive practice and development of an extensive case bank. Furthermore, they highlight the importance of incorporating all the three levels of SA into the student’s training for the employees to understand and perform their tasks correctly. These questions have further been explained and specified by Mason (2020), where for level 1 the question is what, i.e. what do I see/hear, for level 2 the question is so what, i.e. what does it mean for my task, and finally for level 3 it is now

what i.e. what may this result be in the future. Similar Chahar, Hatwal & Sen (2019),

performed a study and concluded that it is important for a company to focus on employee training in order for the employees to become efficient in their work task, which in turn results in organizational output. Moreover, they suggest that a trained staff contributes to a better organizational climate which further results in increased creativity and learning. Chahar et al. (2019) findings also present that by developing employees’ technical and personal skills and abilities will also result in the enhancement of future learning abilities. Additionally, the personnel’s work motivation, job confidence and motivation for the employees to work in different team constellations will increase.

16 2.3.3 Acknowledgment and Responsibility

In order to work with and successfully ensure a stable quality enhancement of the products and within an organization, it is essential to establish a positive human mindset based on participation and individual ownership (Bergman & Klefsjö, 2007). Moreover, Carlzon (1985) presents three key factors for establishing a quality enhancement, which is communication, delegation and education. These three key factors fall in line with the formulation of how to work with the enhancement of quality from Bergman & Klefsjö (2007). They highlight the importance for an employee to feel recognized, have a professional pride related to their work tasks and being premiered for well-performed tasks.

According to Bergman and Klefsjö (2007), participation and commitment of the employees can be reached through a mix between delegation of responsibility and authority within the company. The authors also clarify that it is not the amount of work assignments that are important, but instead its importance, significance, level of encouragement and stimulus for the operator. Moreover, Bergman and Klefsjö (2007) created a figure, displaying the results of trusting and not trusting the employees of a company, displayed in Figure 6. It displays that good confidence in the management results in a delegation of work, motivated employees and better result. At the same time the opposite, which means when the management does not have good confidence, controls the employees and the employees lose their motivation, result in an impaired result. The goal of the company is to work according to the good circle and reinvent all processes following the bad circle into the good circle instead.

Figure 6 The good and bad circle, adapted from Bergman & Klefsjö (2007) 2.3.4 Factors Affecting Human Performance

According to the model by Endsley (1995) in Fel! Hittar inte referenskälla.Figure 5, different factors can affect the performance of an employee, for example stressors and workload. This section presents theories and information regarding some of these factors.

Stress is a widely known concept used to describe the feeling caused by external or internal stressors that usually decrease the human’s performance, attention span, SA

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and decision-making processes (Wickens & Hollands, 1999). Typical stressors that can be found in the workplace, and everyday life, are noise, vibrations, time pressures, bad lighting settings and psychological factors (Wickens & Hollands, 1999). Examples of psychological factors can be anxiety, fatigue or frustrations (Wickens & Hollands, 1999). According to Guastello (2013), is personnel that are working under stressful conditions with uncontrolled and unexpected stressors more likely to display greater negative performance than personnel working in conditions with known stressors. Stressful conditions during work or work-related stress occur when the worker is exposed to high or low pressure and workload, but also challenges that go over their knowledge and coping abilities (Souza‐Talarico, et al., 2020). Furthermore, Wickens & Hollands (1999) presents theories regarding the relation between training and stress monitoring. They state that repetitive training and learning of new scenarios increase the confidence and skill level of the personnel. This in connection to the three levels of human errors earlier presented by Wickens & Hollands (1999), which are skill-rule- and knowledge-based errors. There they state that a clear linear connection of stress-imposed errors is to be found concerning the three different cognitive levels, where highly skilled personnel are less likely to be affected by surrounding stressors then novices. An expert can replace knowledge-based tasks with skill or rule-based decisions and thus minimize the mental resources and focus all resources at the task at hand. By only focusing on the task at hand, the possibilities of making errors is minimized. Another factor connected to stress, which can be both positive and negative for the human performance, is the consequences of workload. When the term workload is connected to areas like boredom, fatigue or sleep loss it usually imposes a negative effect on the performance, but if it is based on an efficient and stimulating effects, it is considered to be positive (Wickens & Hollands, 1999). Passive jobs, or low strain jobs with low workload, are usually defined by low control or with low demands (Souza‐ Talarico, et al., 2020). This results in boredom and unused potential, while active jobs are defined by high demands and high job controls (Souza‐Talarico, et al., 2020). According to Guastello (2013), the physical and mental workload is not only related to the amount of work but also the speed of the work. Thus, it is important to establish an optimal level of workload for the operators to increase the performance and minimize errors. Robert & Hockey (1997) also highlights the importance of understanding the individual factor while discussing workloads, since all humans have their unique limitation.

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3

Method and Implementation

The methodological approach of the study is described in this section. How the research is linked to the method, the case study and literature review is described here and the implementation and analysis. The chapter ends with a discussion about the validity and reliability of the thesis.

3.1

The approach chosen for this study was of qualitative and action research character. An action research approach illustrates how the researchers act in a situation and aims to solve two main goals (Lindström, et al., 2019). These goals were to solve the problem and have a contribution to the knowledge, and the action research includes interaction and collaboration with the personnel (Lindström, et al., 2019). Qualitative research is, according to Yin (2016), used when an understanding of how people cope in a real-world setting is needed. Since the topic of this project was strongly related to humans and how they operate and cooperate, this method was suitable for this project. A literature review was conducted in some specified areas with contributing subcategories. The qualitative research also included a case study, which in turn included a current status analysis and a data collection. It was done through polls and information gained from personnel at the focal company. The process of the work can be seen in Figure 7.

Figure 7 Work process

3.1.1 Link Between Methods and Research Questions

To be able to fulfill the purpose of the study, three different research questions (RQ) were created. To answer them, a literature review and a case study, which contained of a data collection and a current status analysis, were made. How these methods contributed to answer the different RQ is shown below.

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Research question 1 – which problem areas can be identified within the goal towards zero defects in the assembly?

• Literature review

Research question 2 – which of the specified problem areas can be identified to have the most effect of the goal of zero defects?

• Literature review • Case study

Research question 3 – how can the specified problem areas be supported by the suggested improvements?

• Literature review • Case study • Findings

By answering RQ 1, suggestions for RQ 2 were provided and the second question was also able to be answered. The information gained from these two contributed to answer RQ 3.

3.2

The literature review started with a pre-study which was made to identify different problem areas connected to zero defects. This was followed by a literature search to be able to define and delimit the problem, to gain a deeper knowledge of each subject found and to have theories to base decisions on. To be able to identify relevant search fields, brainstorming was used. The brainstorming process is a method where ideas from different people are spontaneously exchanged to be able to solve a problem (Xianghua, Jiansheng, Fulin, Li, & Quande, 2018). The brainstorming session, together with the pre-study, led to several different areas from which three specific search fields where chosen; ZDM, quality and human factors. Several subheadings within these three fields were also investigated.

To further guarantee that all research fields were covered, the snowballing technique and the bibliography review was used, and the information gained was analyzed by coherence, relevance and adequacy (Booth, Papaioannou, & Sutton, 2016; Leedy & Ormrod, 2005). In the selection of relevant topics, related terms and synonyms were also used, considered and included in the research. The research was narrowed down by focusing on literature written from 2000 and forward, with some expectations. This was also done to be able to ensure the validity and reliability of this paper. A representation of the entire process is displayed in Figure 8. The review was mainly based on books and scientific papers, and the sources were found at Jönköping University’s library and through the Scopus database. The pre-study and the literature review were based on different search fields in Scopus, which in turn had specified search terms. All these are listed below.

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Figure 8 Literature review process, based on Booth et al. (2016).

For the pre-study, specified search areas were used within the field of zero defect manufacturing with the following search terms:

• Zero AND defects

• Zero AND defect AND manufacturing

• “Zero defect manufacturing”

• “Zero defects”

• “Zero defects” AND production

Since quality was one main focus area for the project, a literature search on that topic was made. The literature supported already known facts and contributed to new facts that helped the continuation of the research. The Scopus search for all specific topics included the search terms listed below.

Quality:

• Quality

• Quality AND improvement

• Production AND quality

• “Total quality management” Failure mode and effect analysis (FMEA):

• FMEA

• Failure AND mode AND effect AND analysis

• “Failure mode effect analysis”

• FMEA AND production

• FMEA AND risk AND mitigation Supplier quality:

• “Supplier quality” • Supplier AND quality • Supplier AND effects

21 Internal quality assurance:

• Quality AND assurance • “Internal quality” • “Quality assurance”

• “Quality assurance” AND lean

Since the field of human factors also was a key factor in the research, additional literature searches were made for that area. The Scopus search was narrowed down to theories related to specific fields listed below and begun with the search within the human factor field.

Human factors:

• “Human factors” Human errors:

• Human AND error

• Skill AND rule AND knowledge-based AND behaviors

Situation awareness:

• Situation AND awareness

• Situation AND awareness AND manufacturing

• Situation AND awareness AND level

• Learning AND training AND employees Performance:

• Performance

• Cognitive AND stress AND performance

• “Human performance” AND workload

3.3

This project contained a case study performed at a focal company. The case study approach was chosen since it contributed to the holistic view of the problem and gave the authors the possibility to collect a lot of information (Patel & Davidson, 2011). The case study started with a company presentation and a company tour, which gave a holistic view of the company, its products and processes. It helped with the understanding of how the focal company was structured and how the working process was organized. This was followed by a deeper understanding of different problem areas at the company. This was an important step to reach the knowledge of where the main problems occurred and was made through information collection from different fields at the focal company. Unstructured and unstandardized interviews were made with the personnel in the assembly, with easy questions, to get a holistic view of their thoughts and feelings of where problems may occur. This was made initially in the project to get a general understanding of them company and its work process. The method of using unstructured and unstandardized interviews i.e. qualitative interviews, enables the respondents to answer freely to the questions, which is a useful method when collecting interpretations and thoughts about a specific phenomenon (Patel & Davidson, 2011).

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This was followed by a deeper investigation through polls and surveys to be able to detect specific problem areas.

3.3.1 Case Company

The focal company used for this project was a company that works within product development, manufacturing and marketing in the lighting areas. The company supported the case study by constructing a project group in which the authors were included. The project group contained of a project leader, which was a quality and environment manager, two production leaders, two team leaders from the assembly, two from customer design adoption, one from quality and one production engineer. Meetings were held weekly in the project group and these meetings also functioned as gates to ensure that the project was following the time frame and the progress. Data was collected from different departments and analyzed both by the authors, but also together in the group where issues were presented and discussed. These meetings constantly guided the project on its way towards the result.

To establish the needed knowledge from the focal company, the department of assembly and production was chosen as the unit of analysis in the case study. The assembly at the focal company consisted of multiple manually cells and lines, where the lines produced according to a set takt time and the cells according to the number of orders. Even though the workload and types of produced products differentiated between the assembly settings, i.e. cells and lines, the operators rotated both between the stations and between the areas at the company. This could be problematic since the workers need knowledge within several different areas and products. To get a realistic output from the case, one cell and one line were examined so both similarities and differences of the workers and the structures were accounted for.

3.4

The data collection process started with group meetings together in the project group. Through the meetings, it was decided to move forward with polls, surveys and questioners. According to Patel & Davidson (2011), it ensures an accurate information collection of the current situation at the assembly, where the sampled data could be collected from the workers at the actual assembly units. The polls and questioners were made to get accurate information through closed and open questions (Patel & Davidson, 2011). An overview of the problem areas found in the theory and at the focal company, and how they are linked with the data collection of the project, is being displayed below in Table 8.

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Table 8 Map of the linkage between problem areas and data collection

Problem areas from theory and focal company _Lite ra tur e sear ch Di sr u p ti o n pol l In str u ctio n fa ilu re p o ll Sur ve y As se m b ly In str u ctio n Ob se rv at io n da ta Cl ai m d at a Co m p et en ce assessm en t Assembly instructions X X X X X X Introduction for new employees X X X Competence of the employees X X X X X Technical assistance tools X X X X Supplier quality X X X X Internal quality assurance X X X X X

3.4.1 Disruption Poll

The first poll focused on problems that occurred in the cell or the line. The operators marked every disruption and marked what kind of disruption, for example if it was damage from supplier, mistakes made by an operator or faults in the assembly instructions. The full version of the poll and the result can be seen in appendix 7.1. This was done for four weeks.

3.4.2 Instruction Failure Poll

The second poll had more open questions where the operators wrote information about the faults that occurred. It contained information like how the problem or error occurred, what type of error it was, where it occurred, etc. This gave information about the different types of problems and why they happened, which was the information needed to be able to continue the analysis of this problem area. This poll was performed for three weeks in one cell and one line at the focal company. Afterward, the different problems were classified in different categories based on what kind of problem the operators had, and it was done together with specialized personnel who knew what problem could be connected to what category. The full version of the poll can be seen in appendix 7.2.

3.4.3 Survey Assembly Instruction

A survey was made specifically about the assembly instruction field. The survey was designed based on the current situation in the assembly at the focal company, suggestions from the project group and collected theory. The questionnaire was structured with yes and no questions and ended with two more open questions. This gave the respondent opportunities to think outside the box and provide input from real-life situations. The survey was distributed to a group of operators from a total of 5 units of the assembly to collect as many results as possible. Moreover, by extending the respondents group, the result was assumed to be more realistic since the workers rotate between the areas. The handout and mix of the operators were made of the team leader,

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since they know their staff’s abilities. This to get answers both from personnel with advanced knowledge within the field of assembly instructions, and from personnel that had less knowledge. The survey can be found in appendix 7.3.

3.4.4 Documentation of Observation Data

To gain a deeper understanding of errors that occurred in the assembly, which in turn can result in claims to the customers, a collection of the focal company’s observation data was made. The observation data file was provided by the company from their server where they log control data from previous and ongoing productions. The file was created through a summary of all the previous mistakes and errors found at the plant. When an error or mistake occurred in the assembly, a form was filled in that shows who made the observation, where it occurred, a short description of the problem and to what category it belongs. Examples of different categories can be faults from suppliers, material damage or faults in the assembly instruction.

Since this project only focuses on one cell and one line, these stations were sorted out and only data from them were analyzed. As described above, the operators selected one category for each fault, and later the authors analyzed and sorted out the information into pre-defined categories. This gave a holistic view of what kind of problems that occurred and what field they belonged to. It also clarified which problem area, based on only these observations, that resulted in most problems for the cell or the line. The data was limited to 2019 since that was expected to give a suitable amount of data possible to investigate. To only focus on 2019 and not earlier also ensured that only relevant faults were analyzed, which made the data more reliable.

3.4.5 Documentation of Claim Data

To be able to reach the goal of this study and identify critical areas affecting ZDM, the claim data was of great importance. Thus, the focal company’s database was used to search for documentation of the registered claims reported by the customers. In order to get relevant results, the document was first filtered based on both the year 2019 and the two examined units. The filtration however needed to be revised, due to insufficient results. Therefore, the filtration was restricted to only filtering based on the year 2019, which meant that all lines and cells were included. The resulting output were categorized into categories depending on the identified defects and types of claim. Examples of defects could be incorrect placed part, missing component and incorrectly programmed driver. When the result was sorted out, it was easily seen which categories contained most claims.

3.4.6 Competence Assessment

Furthermore, a competence assessment of the workers was made through a poll administrated by the production leaders. The assessment was made to establish a deeper understanding of what knowledge the working personnel possessed. It was done through an anonymous poll, where the competence of drawing, electrical safety and electrostatic discharge (ESD) were listed in three different columns and a line was drawn in respectively row for each employee who possessed this competence. This was

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done by the team leader for the cell and the line to get an objective result. The full poll and answers can be found in appendix 7.6.

3.5

In order to create well-grounded statements and conclusions regarding the root causes of the different investigated problem areas, the collected data was turned into diagrams and graphs, to establish a better overview. The different data collection methods and results were then compared to one another and discussed in the project group. Based on the discussion, problem areas were selected as the focus for prevention work. The decision was based on the results of the collected data.

To further confirm the underlying causes of the problems within the chosen areas, fishbone diagrams, 5 why analyses and process FMEA were created. These methods were chosen through discussion within the project group, based on the findings from the literature review and previous knowledge of the team members in the group. 3.5.1 Fishbone Diagram

To further understand the different factors within each of the concerned areas, two fishbone diagrams were conducted. The fishbone method, or Ishikawa diagram as it also is called, is a method used for identifying the root cause of a specified problem (Tongyuan, Chao, & Lixiang, 2018). The model indicates the relationship between the problem and its underlying causes through analyzing of relevant factors and its subareas and underlaying reasons (Tongyuan, Chao, & Lixiang, 2018).

The problems chosen for further examination were assembly instruction and lapses or mistakes, connected to both the competence of the employees and introduction for new employees. Each problem was then individually discussed based on five different aspects, which were; human, equipment, material, method and management. The result was then transferred into a template for the method to get a holistic overview. The models were then discussed based on assumptions of severity, reliability and occurrences of the individual factors and underlying causes. The models and results can be seen in appendix 7.7.

3.5.2 5 Why Analysis

To further understand the underlying causes and problems concerning the assembly instructions, a 5 why analysis was made based on five random errors which occurred the cell and the line. A 5 why analysis is a method used to explore the cause- and effect relationship of a problem with the help of an interrogative approach (Gangidi, 2019). By repeating “why” five times, the origin of the problem and its solutions became clear (Gangidi, 2019). To get a thorough understanding of different rout-causes and their effect, multiple 5 whys was constructed regarding the problem of incorrect assembly instructions.

A decision was made by the project group to select the five problems representing a production in practice, which meant not a tempered or tailored decision, to obtain a better result. Therefore, the first five problems, which occurred between the cell and the

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line, was selected without any adjustments. When each problem was identified, the first step was to identify the main error and then move on to ask the first why, which meant asking why this happened. This question was then repeated four times in order to get closer too and uncover the core problem for each error. When the underlying error factor was identified, a discussion was held within the group to find a prevention or solution for each core problem. The full 5 why analysis can be found in appendix 7.8.

3.5.3 FMEA

In the assembly, two different failure mode and effect analysis (FMEA) was done. The FMEA was done at the process of assembling a lamp and before the FMEA was started, the authors ensured that the steps in Table 1 were thoroughly reviewed and understood. The selection of lamps was made based on pre-defined criteria, for example the lamp needed to be assembled in a batch bigger than a few lamps to ensure the validity of the FMEA. It was done by the personnel with knowledge of the lamps and the assembly for the analysis to be as accurate as possible. Besides that, a lamp that was not completely new for the operators was chosen.

During the analysis, the authors observed the process carefully. Every process step was noticed and written down in the FMEA form. To ensure that no step was forgotten, every process step was viewed several times and the operators explained what was done and how. After that, all possible failures that could occur in every step were discussed and noticed in the form. This was done by the performer of the FMEA, but with input from the operators who knew about the problems. The next step was to analyze the effects of every failure and to assess the severity if they occur. That was followed by an analysis of the cause of the failures and assessment of the occurrence. Also, a check if there were any current control of the steps, and the assessment of detectability of the failure was made. These assessments were done by using numbers between 1-10, where 1 is no risk and 10 is a very high risk. These three numbers for every step were multiplied with each other and resulted in an RPN number. The action with the highest RPN was the action with the highest risk. The FMEA form can be found in appendix 7.9.

3.6

Research of this kind should evaluate the ethical factors as one vital part of the study (Creswell, 2009). Since the research was included in a project at a company and involves supervisors both from the school and the company, biases are unavoidable. To be able to avoid biases as much as possible, different kinds of data were collected and several different methods were used. All participants in the polls and interviews contributed anonymously and voluntarily. No data about the participants were collected or used and they chose by themselves if they wanted to answer the questions or not. To further ensure the ethical strength of the study, the four ethical aspects for research, described by Patel & Davidson (2011), has been taken into consideration. These aspects describe how to handle information, consent, confidentiality and utilization through an ethical perspective. All data has been managed based on these criteria and the company