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Title: Product lifecycle optimisation of car climate controls using analytical hierarchical process (Ahp) analysis and a multi-objective grouping genetic algorithm (mogga)
Authors: Lee, Michael J.
Case, Keith
Marshall, Russell
Issue Date: 2016
Publisher: © School of Engineering, Taylor’s University
Citation: LEE, M.J., CASE, K. and MARSHALL, R., 2016. Product lifecycle optimisation of car climate controls using analytical hierarchical process (Ahp) analysis and a multi-objective grouping genetic algorithm (mogga). Journal of Engineering Science and Technology, 11(1), pp. 1-17.
Abstract: © School of Engineering, Taylor’s University. A product’s lifecycle performance (e.g. assembly, outsourcing, maintenance and recycling) can often be improved through modularity. However, modularisation under different and often conflicting lifecycle objectives is a complex problem that will ultimately require trade-offs. This paper presents a novel multi-objective modularity optimisation framework; the application of which is illustrated through the modularisation of a car climate control system. Central to the framework is a specially designed multi-objective grouping genetic algorithm (MOGGA) that is able to generate a whole range of alternative product modularisations. Scenario analysis, using the principles of the analytical hierarchical process (AHP), is then carried out to explore the solution set and choose a suitable modular architecture that optimises the product lifecycle according to the company’s strategic vision.
Description: This paper was published in the journal Journal of Engineering Science and Technology
Version: Published
URI: https://dspace.lboro.ac.uk/2134/20300
Publisher Link: http://jestec.taylors.edu.my/Vol%2011%20issue%201%20January%202016/Volume%20(11)%20Issue%20(1)%20001-%20017.pdf
ISSN: 1823-4690
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)
Published Articles (Design School)

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