Simultaneous optimisation of products, processes, and people in development projects
Organisations involved in product development (PD) constantly introduce new products using development teams within the organisation. These teams carry out PD activities using the established development processes in order to produce new products. Traditionally, these three domains (product, process...
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Veröffentlicht in: | Journal of engineering design 2013-04, Vol.24 (4), p.272-292 |
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Sprache: | eng |
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Zusammenfassung: | Organisations involved in product development (PD) constantly introduce new products using development teams within the organisation. These teams carry out PD activities using the established development processes in order to produce new products. Traditionally, these three domains (product, process, and people) are treated separately and individual optimisation is attempted for each domain (i.e. without regard for the other two domains). The result is a group of three individual-domain optimal solutions instead of a single-multi-domain optimal solution. The main objective of this paper is to formulate and find the multi-domain optimal solution for a PD project. The inter- and intra-dependencies within and between the three domains are captured using the design structure matrix. Then three relational rules that relate the domains together are proposed to help formulate a multi-domain optimisation objective function. The proposed methodology offers PD managers with a practical tool to identify hidden improvement opportunities or mitigate development risks that lie at the intersection of two or more domains. To solve this problem, eight heuristic search methods based on improvement and constructive heuristics are proposed. We test the performance of the proposed heuristics on 60 examples with varying sizes and show a trade-off between the eight heuristics based on solution accuracy and computational expense. Our analysis shows that the best improvement heuristic using a constructive approach provides good solutions (i.e. 12% deviation from known optimal solution) using a small number of computations (i.e. only 104 iterations). |
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ISSN: | 0954-4828 1466-1837 |
DOI: | 10.1080/09544828.2012.727206 |