A new configuration approach to support the technical bid solutions for complex ETO products under uncertainties

Haizhu Zhang, Rong Li*, Shengfeng Qin, Jian Wang, Lifei Zhu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This paper proposes a novel two-stage and multi-objective optimization design method for the configuration design of complex engineering-to-order (ETO) product under imprecise matching and other uncertainties. The goal is to support selection of the optimal technical bid solutions while meeting requirements. A new two-stage configuration design framework for complex ETO products is proposed. Stage one is product architecture configuration design, supported by an engineering characteristics design method based on constraint satisfaction problems and Bayesian networks, and stage two is physical module configuration design, where a multi-objective optimal configuration model of physical modules is developed with the goals of minimum production cost, shortest delivery time, and maximum degree of matching technical requirements under imprecise matching of technical requirements and uncertainties in such as production cost and delivery time. As for the new selection method for obtaining an optimal technical bid solution scheme, it integrates a non-dominated sorting genetic algorithm (NSGA-II) and an approximate ideal solution ranking method (TOPSIS). Our approach has been applied to the design of a technical bid solution of subway’s bogie. The results show that this approach enables bidders to quickly select the most interesting solution during a bidding process. The proposed approach aids the bidders to quickly create ETO product scheme designs, and then advise a new selection method for the bidders to quickly obtain a technical bid solution from the above product scheme designs, which has a minimum cost while meeting order requirements.

Original languageEnglish
Pages (from-to)3413-3434
Number of pages22
JournalInternational Journal of Advanced Manufacturing Technology
Volume129
Issue number7-8
Early online date27 Oct 2023
DOIs
Publication statusPublished - 1 Dec 2023

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