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Title: Product modularity : a multi-objective configuration approach
Author: Lee, Michael
ISNI:       0000 0004 2686 849X
Awarding Body: Loughborough University
Current Institution: Loughborough University
Date of Award: 2010
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Product modularity is often seen as a means by which a product system can be decomposed into smaller, more manageable chunks in order to better manage design, manufacturing and after-sales complexity. The most common approach is to decompose the product down to component level and then group the components to form modules. The rationale for module grouping can vary, from the more technical physical and functional component interactions, to any number of strategic objectives such as variety, maintenance and recycling. The problem lies with the complexity of product modularity under these multiple (often conflicting) objectives. The research in this thesis presents a holistic multi-objective computer aided modularity optimisation (CAMO) framework. The framework consists of four main steps: 1) product decomposition; 2) interaction analysis; 3) formation of modular architectures and; 4) scenario analysis. In summary of these steps: the product is first decomposed into a number a basic components by analysis of both the physical and functional product domains. The various dependencies and strategic similarities that occur between the product s components are then analysed and entered into a number of interaction matrixes. A specially developed multi-objective grouping genetic algorithm (MOGGA) then searches the matrices and provides a whole set of alternative (yet optimal) modular product configurations. The solution set is then evaluated and explored (scenario analysis) using the principles of Analytic Hierarchy Process. A software prototype has been created for the CAMO framework using Visual Basic to create a multi-objective genetic algorithm (GA) based optimiser within an excel environment. A case study has been followed to demonstrate the various steps of the framework and make comparisons with previous works. Unlike previous works, that have used simplistic optimisation algorithms and have in general only considered a limited number of modularisation objectives, the developed framework provides a true multi-objective approach to the product modularisation problem.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available