A QUALITY ENGINEERING FRAMEWORK FOR AUTOMOTIVE MANUFACTURING SMEs

Flowers, Michael

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A QUALITY ENGINEERING FRAMEWORK FOR AUTOMOTIVE MANUFACTURING SMEs

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Flowers, Michael (2022) A QUALITY ENGINEERING FRAMEWORK FOR AUTOMOTIVE MANUFACTURING SMEs. PhD thesis, University of Gloucestershire. doi:10.46289/ZIUK5938

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Official URL: https://doi.org/10.46289/ZIUK5938

Abstract

Compared to large automotive manufacturing organisations, SMEs within the industry significantly differ in their business models and operations environments and are generally too constrained to dedicate their limited financial and workforce capabilities to the implementation of the often capital-intensive, complex, laboriously demanding, time-consuming and expert-biased industry standard and mainstream quality systems. The goal of this research was to explore the development of a novel quality engineering framework, which is tailored to SMEs’ general available resources and characteristics, and essentially features the highest-level properties of maximised organisation-wide strategy to achieve a robust, scalable quality-focused manufacturing environment cost-effectively. To achieve this goal, it was necessary to (1) identify the time-dependent variants of quality performance, (2) map out the factors that cause non-Quality Management System (QMS) compliant firms to deliver less quality target value better than firms in the QMS league, (3) identify the variables that impede the hybridisation and implementation of QMS, (4) identify human-biased vectors of quality data deviations (vQDD), and (5) convert the findings in (1) to (4) into key input parameters required for the development of the proposed framework. To extract original objective input data empirically, this study took a paradigm shift by viewing automotive manufacturing as a social phenomenon, so far underestimated or uncharted, with which personnel or social (human) actors interact to socially construct knowledge and reality based on their experiences with the quality dimensions and quality system structures. This research utilised a pragmatic and concurrent transformative mixed-methods design approach for the primary quantitative and qualitative data acquisition from non-probabilistic cohorts of consumers of automobile products and services, and experts across automotive manufacturing and service sectors in Africa, Asia, Europe, the Middle East, and North America. The data collection instruments were formalised for (1) Quality Dimensions – mapped against Management Role, Quality of Service, Continuous Monitoring and Emerging Technologies, and (2) Indices of Quality Performance – oriented on QMS Knowledgebase, Quality Design, Standards Implementation and Responses to Threats. The outcomes were translated and coded into functional requirement (FR) notations and their corresponding plausible design parameters (DP). The hierarchies of their FR-DP decomposition were identified and exhausted. The application of Axiomatic Design Theory was extended to integrate the results as key input parameters for the development of a novel QMS-based quality engineering framework, which is tailored to the resources and characteristics of SMEs. The subsequent review of the quality engineering framework substantiated the comprehensibility, scalability and applicability of the framework. The outcome of this research, which evolved methodically from the synthesis of the findings extracted from the empirical data, shows that a significant amount of quality issues arises as a result of social (human) actors’ adversarial or apathetic behaviours towards quality goals within the social construct of automotive manufacturing organisations. This body of knowledge is also complemented with plausible sets of mitigation solutions mapped against human-oriented vQDD. The framework further highlights a preference for (1) countermeasures against customer-centric demand uncertainties, (2) alignment with industry standard quality procedures, and (3) reconfigurability and robustness in order to capture and address any emerging issues during the initial design, in-process and or post-process stage. The analysis and relevance of the overall findings is evidenced by the possibility to integrate them to address SMEs’ general need for a flexible-to-implement, cost-time-resource-effective and easily adaptable quality framework. This draws the conclusion that this quality engineering framework provides a well-structured methodology to action-guide SMEs within the automotive manufacturing industry to establish their in-house, customised, and robust QMS for quality implementation across all facets of their manufacturing operations at minimal costs. Furthermore, the scalability and reconfigurability nature of the framework, which falls within the current understandings of the dynamics of automotive quality engineering, shows that it is not only for SMEs but can also be extended and adopted for its application in large automotive manufacturing organisations and other sectors.

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Thesis (PhD)

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