TY - JOUR
T1 - A new configuration approach to support the technical bid solutions for complex ETO products under uncertainties
AU - Zhang, Haizhu
AU - Li, Rong
AU - Qin, Shengfeng
AU - Wang, Jian
AU - Zhu, Lifei
N1 - Funding information: This work was supported by National Key Research of China (grant number 2020YFB1711402); National Natural Science Foundation of China (grant number 52105277); and Sichuan Provincial Natural Science Foundation (Grant No. 2022NSFSC0038).
PY - 2023/12/1
Y1 - 2023/12/1
N2 - 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.
AB - 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.
KW - ETO products
KW - Multi-objective optimization
KW - Product configuration
KW - Technical bid solution
KW - Uncertainty
UR - http://www.scopus.com/inward/record.url?scp=85174942456&partnerID=8YFLogxK
U2 - 10.1007/s00170-023-12472-0
DO - 10.1007/s00170-023-12472-0
M3 - Article
AN - SCOPUS:85174942456
SN - 0268-3768
VL - 129
SP - 3413
EP - 3434
JO - International Journal of Advanced Manufacturing Technology
JF - International Journal of Advanced Manufacturing Technology
IS - 7-8
ER -