The automotive manufacturing facility is extremely complex and expensive system. Managing and understanding the dynamics of automotive manufacturing is a challenging endeavour. In the current era of dynamic global competition, a new concept such as Collaborative Lean Manufacturing Management (CLMM) can be implemented as an alternative for organisations to improve their Lean Manufacturing Management (LMM) processes. All members in the CLMM value chain must work together towards common objectives in order to make the LMM achievable in the collaborative environment. The novel research approach emphasises the use of Knowledge-Based (KB) approach in such activities as planning, designing, assessing and providing recommendations of CLMM implementation, through: a) developing the conceptual CLMM model; b) designing the KBCLMM System structure based on the conceptual model; and c) implementing Gauging Absences of Pre-requisites (GAP) analysis and Analytic Hierarchy Process (AHP) approach in the hybrid KBCLMM. The development of KBCLMM Model is the most detailed part in the research process and consists of five major components in two stages. Stage 1 (Planning stage) consists of Organisation Environment, Collaborative Business and Lean Manufacturing components. Stage 2 (Design stage) consists of Organisation CLMM Capability and Organisation CLMM Alignment components. Each of these components consists of sub-components and activities that represent particular issues in the CLMM development. From the conceptual model, all components were transformed into the KBCLMM System structure, which is embedded with the GAP and AHP techniques, and thus, key areas of potential improvement in the LMM are identified for each activity along with the identification of both qualitative and quantitative aspects for CLMM implementation. In order to address the real situation of CLMM operation, the research validation was conducted for an automotive manufacturer¿s Lean Manufacturing Chain in Malaysia. Published case studies were also used to test several modules for their validity and reliability. This research concludes that the developed KBCLMM System is an appropriate Decision Support System tool to provide the opportunity for academics and industrialists from the fields of industrial engineering, information technology, and operation management to plan, design and implement LMM for a collaborative environment. / Universiti Utara Malaysia and Ministry of Higher Education of Malaysia

The automotive manufacturing facility is extremely complex and expensive system. Managing and understanding the dynamics of automotive manufacturing is a challenging endeavour. In the current era of dynamic global competition, a new concept such as Collaborative Lean Manufacturing Management (CLMM) can be implemented as an alternative for organisations to improve their Lean Manufacturing Management (LMM) processes. All members in the CLMM value chain must work together towards common objectives in order to make the LMM achievable in the collaborative environment. The novel research approach emphasises the use of Knowledge-Based (KB) approach in such activities as planning, designing, assessing and providing recommendations of CLMM implementation, through: a) developing the conceptual CLMM model; b) designing the KBCLMM System structure based on the conceptual model; and c) implementing Gauging Absences of Pre-requisites (GAP) analysis and Analytic Hierarchy Process (AHP) approach in the hybrid KBCLMM. The development of KBCLMM Model is the most detailed part in the research process and consists of five major components in two stages. Stage 1 (Planning stage) consists of Organisation Environment, Collaborative Business and Lean Manufacturing components. Stage 2 (Design stage) consists of Organisation CLMM Capability and Organisation CLMM Alignment components. Each of these components consists of sub-components and activities that represent particular issues in the CLMM development. From the conceptual model, all components were transformed into the KBCLMM System structure, which is embedded with the GAP and AHP techniques, and thus, key areas of potential improvement in the LMM are identified for each activity along with the identification of both qualitative and quantitative aspects for CLMM implementation. In order to address the real situation of CLMM operation, the research validation was conducted for an automotive manufacturer's Lean Manufacturing Chain in Malaysia. Published case studies were also used to test several modules for their validity and reliability. This research concludes that the developed KBCLMM System is an appropriate Decision Support System tool to provide the opportunity for academics and industrialists from the fields of industrial engineering, information technology, and operation management to plan, design and implement LMM for a collaborative environment.

The product development process for the automotive industry is normally complicated, lengthy, expensive, and risky. Hence, a study on a new concept for Low Volume Automotive Manufacturing (LVAM), used for niche car models manufacturing, is proposed to overcome this issue. The development of a hybrid Knowledge Based (KB) System, which is a blend of KB System, Gauging Absences of Pre-requisites (GAP), and Analytic Hierarchy Process (AHP) is proposed for LVAM research. The hybrid KB/GAP/AHP System identifies all potential elements of LVAM issues throughout the development of this system. The KB System used in the LVAM analyses the gap between the existing and the benchmark organisations for an effective implementation. The novelty and differences in the current research approach emphasises the use of Knowledge Based (KB) System in the planning and designing stages by suggesting recommendations of LVAM implementation, through: a) developing the conceptual LVAM model; b) designing the KBLVAM System structure based on the conceptual LVAM model; and c) embedding Gauging Absences of Pre-requisites (GAP) analysis and Analytic Hierarchy Process (AHP) approach in the hybrid KBLVAM System. The KBLVAM Model explores five major perspectives in two stages. Planning Stage (Stage 1) consists of Manufacturer Environment Perspective (Level 0), LVAM Manufacturer Business Perspective (Level 1), and LVAM Manufacturer Resource Perspective (Level 2). Design Stage (Stage 2) consists of LVAM Manufacturer Capability - Car Body Part Manufacturing Perspective (Level 3), LVAM Manufacturer Capability - Competitive Priorities Perspective (Level 4), and LVAM Manufacturer Capability - Lean Process Optimisation Perspective (Level 5). Each of these perspectives consists of modules and sub-modules that represent specific subjects in the LVAM development. Based on the conceptual LVAM model, all perspectives were transformed into the KBLVAM System structure, which is embedded with the GAP and AHP techniques, hence, key areas of potential improvement are recommended for each activity for LVAM implementation. In order to be able to address the real situation of LVAM environment, the research verification was conducted for two automotive manufacturers in Malaysia. Some published case studies were also used to check several modules for their validity and reliability. This research concludes that the developed KBLVAM System provides valuable decision making information and knowledge to assist LVAM practitioners to plan, design and implement LVAM in terms of business organisation, manufacturing aspects and practices.

Friction Bit Joining (FBJ) is a method used to join lightweight metals to advanced high-strength steels (AHSS). The automotive industry is experiencing pressure to improve fuel efficiency in their vehicles. The use of AHSS and aluminum will reduce vehicle weight which will assist in reducing fuel consumption. Previous research achieved joint strengths well above that which was required in three out of the four standard joint strength tests using DP980 AHSS and 7075 aluminum. The joints were mechanically tested and passed the lap-shear tension, cross-tension, and fatigue cycling tests. The t-peel test configuration never passed the minimum requirements. The purpose of continuing research was to increase the joint strength using FBJ to join the aluminum and AHSS the automotive industry desires to use specifically in the t-peel test. In this study FBJ was used to join 7085 aluminum and GADP1180 AHSS. The galvanic coating on the AHSS and its increased strength with the different aluminum alloy required that all the tests be re-evaluated and proven to pass the standard tests. FBJ is a two-step process that uses a consumable bit. In the first step the welding machine spins the bit to cut through the aluminum, and the second step applies pressure to the bit as it comes in contact with the AHSS to create a friction weld.

The product development process for the automotive industry is normally complicated, lengthy, expensive, and risky. Hence, a study on a new concept for Low Volume Automotive Manufacturing (LVAM), used for niche car models manufacturing, is proposed to overcome this issue. The development of a hybrid Knowledge Based (KB) System, which is a blend of KB System, Gauging Absences of Pre-requisites (GAP), and Analytic Hierarchy Process (AHP) is proposed for LVAM research. The hybrid KB/GAP/AHP System identifies all potential elements of LVAM issues throughout the development of this system. The KB System used in the LVAM analyses the gap between the existing and the benchmark organisations for an effective implementation. The novelty and differences in the current research approach emphasises the use of Knowledge Based (KB) System in the planning and designing stages by suggesting recommendations of LVAM implementation, through: a) developing the conceptual LVAM model; b) designing the KBLVAM System structure based on the conceptual LVAM model; and c) embedding Gauging Absences of Pre-requisites (GAP) analysis and Analytic Hierarchy Process (AHP) approach in the hybrid KBLVAM System. The KBLVAM Model explores five major perspectives in two stages. Planning Stage (Stage 1) consists of Manufacturer Environment Perspective (Level 0), LVAM Manufacturer Business Perspective (Level 1), and LVAM Manufacturer Resource Perspective (Level 2). Design Stage (Stage 2) consists of LVAM Manufacturer Capability ¿ Car Body Part Manufacturing Perspective (Level 3), LVAM Manufacturer Capability ¿ Competitive Priorities Perspective (Level 4), and LVAM Manufacturer Capability ¿ Lean Process Optimisation Perspective (Level 5). Each of these perspectives consists of modules and sub-modules that represent specific subjects in the LVAM development. Based on the conceptual LVAM model, all perspectives were transformed into the KBLVAM System structure, which is embedded with the GAP and AHP techniques, hence, key areas of potential improvement are recommended for each activity for LVAM implementation. In order to be able to address the real situation of LVAM environment, the research verification was conducted for two automotive manufacturers in Malaysia. Some published case studies were also used to check several modules for their validity and reliability. This research concludes that the developed KBLVAM System provides valuable decision making information and knowledge to assist LVAM practitioners to plan, design and implement LVAM in terms of business organisation, manufacturing aspects and practices. / Universiti Malaysia Pahang and Ministry of Higher Education Malaysia

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The dissertation "Enhancing Automotive Manufacturing Quality and Reducing Variability Through Six Sigma Principles" provides a thorough analysis of the ways in which Six Sigma techniques can be applied to the automotive manufacturing sector to improve quality control, reduce variability, and boost operational efficiency. Utilizing a diverse of secondary data sources, such as industry reports, case studies, academic research articles, and one-on-one consultations, this study seeks to offer important insights into the implementation and efficacy of Six Sigma principles in the context of automotive manufacturing. By stressing the fundamental ideas of Six Sigma outlined by Deming and Juran and scrutinizing influential works in quality management, the literature study builds a solid theoretical basis. The study's goals and research questions centre on comprehending how Six Sigma improves quality and lowers variability in automobile production processes. This research finds important insights on how Six Sigma may improve quality control, lower process variability, and increase operational efficiency in the automobile manufacturing industry via thorough secondary data analysis. The research offers useful insights into using Six Sigma approaches, emphasizing the significance of staff involvement, data-driven decision-making, and leadership commitment in guaranteeing the success of Six Sigma projects. The thesis ends with suggestions for further research, such as investigating primary data gathering techniques, contrasting this methodology with other approaches to quality management, and using longitudinal analysis to monitor the long-term effects of Six Sigma projects. In summary, this dissertation advances our knowledge of how Six Sigma concepts may be used to promote operational excellence and continuous improvement in the automobile manufacturing sector. It also provides practitioners and stakeholders in the industry with insightful information

No / A conceptual design approach is an important stage for the development of a hybrid Knowledge-Based System (KBS) for Low Volume Automotive Manufacturing (LVAM). The development of a hybrid KBS, which is a blend of KBS and Gauging Absences of Pre-requisites (GAP), is proposed for LVAM research. The hybrid KB/GAP system identifies all potential elements of LVAM issues throughout the development of this system. The KBS used in the system design stage of the LVAM system analyses the gap between the existing and the benchmark organisations for an effective implementation through the GAP analysis technique. The proposed KBLVAM model at the design stage explores three major components, namely LVAM car body parts manufacturing perspective, LVAM competitive priorities perspective and LVAM lean environment perspective. Initial results reveal that the KBLVAM system has identified, for each perspective modules and sub-modules, the Problem Categories (PC) in a prioritised manner. / The financial support by the Malaysian Government, Universiti Malaysia Pahang and University of Bradford for this research is grateful acknowledged.

This thesis is a case study conducted at Magna Electronics to explore the use of machinelearning techniques in improving the predictive quality of electronic control unit (ECU)within the automotive manufacturing. This thesis aims to apply interpretable machinelearning methods to predict potential future ECU failures early. With the interpretablemachine learning the goal is to identify predictive variables that lead to ECU failure andwhich can be used as support for decision making.Logistic Regression and Random Forest were chosen as the machine learning methods,which have been used in research of predictive quality and have different levels of interpretability.TreeSHAP was used on the Random Forest as the post-hoc method to furtherunderstand the results. The models’ performances were quantitatively evaluatedthrough metrics such as accuracy and area under precision-recall curve. Subsequently, thebest-performing models were further analyzed using confusion matrices, precision-recallcurves, and horizontal bar charts to assess the impact of predictive variables.The results of this thesis indicated that while Random Forest outperformed Logistic Regression,both models demonstrated limited capability in accurately predicting faulty ECUs,due to the low AUCPR scores. The precision-recall curves suggested performance near randomguess, highlighting the possible variability in parameter impact.This study has also identified significant challenges, such as data imbalance and mislabeling,which may have had a negative effect on the results. Given these issues, the thesisadvises caution in using these results for decision-making. Although, findings of this thesisunderscore the need for a cautious approach to interpreting model outputs, suggestingthat real-world application may require to use different models based on the specific goalsand context of the analysis.

Friction bit joining (FBJ) is a new method that enables lightweight metal to be joined to advanced high-strength steels. Weight reduction through the use of advanced high-strength materials is necessary in the automotive industry, as well as other markets, where weight savings are increasingly emphasized in pursuit of fuel efficiency. The purpose of this research is twofold: (1) to understand the influence that process parameters such as bit design, material type and machine commands have on the consistency and strength of friction bit joints in dissimilar metal alloys; and (2) to pioneer machine and bit configurations that would aid commercial, automated application of the system. Rotary broaching was established as an effective bit production method, pointing towards cold heading and other forming methods in commercial production. Bit hardness equal to the base material was found to be highly critical for strong welds. Bit geometry was found to contribute significantly as well, with weld strength increasing with larger bit shaft diameter. Solid bit heads are also desirable from both a metallurgical and industry standpoint. Cutting features are necessary for flat welds and allow multiple material types to be joined to advanced high-strength steel. Parameters for driving the bit were established and relationships identified. Greater surface area of contact between the bit and the driver was shown to aid in weld consistency. Microstructure changes resulting from the weld process were characterized and showed a transition zone between the bit head and the bit shaft where bit hardness was significantly increased. This zone is frequently the location of fracture modes. Fatigue testing showed the ability of FBJ to resist constant stress cycles, with the joined aluminum failing prior to the FBJ fusion bond in all cases. Corrosion testing established the use of adhesive to be an effective method for reducing galvanic corrosion and also for protecting the weld from oxidation reactions.