Joint optimization of complex product variant design responding to customer requirement changes-Reference-Cited by-同舟云学术

Joint optimization of complex product variant design responding to customer requirement changes

Published:2015-10-06 Issue:1 Volume:30 Page:397-408
ISSN:1064-1246
Container-title:Journal of Intelligent & Fuzzy Systems
language:
Short-container-title:IFS

Author:

Guodong Yu¹,Yu Yang²,Aijun Liu³

Affiliation:

1. Department of Industrial & Systems Engineering, National University of Singapore, Singapore

2. State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China

3. Department of Supply Chain Management, W. P. Carey School of Business, Arizona State University, Arizona, USA

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference26 articles.

1. Requirements-based development of an improved engineering change management method;Hamraz;Journal of Engineering Design,2013

2. A process oriented hybrid resource integration framework for product variant design;Li;Journal of Computing and Information Science in Engineering,2012

3. Extracting assembly mating graphs for asbly variant design;Sambhoos;Journal of Computing and Information Science in Engineering,2009

4. The application of product variant design based on case-based design in the development of stone equipments;Wang;Advances in Materials Manufacturing Science and Technology,2004

5. Change and customization in complex engineering domains;Eckert;Research in Engineering Design,2004

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Research on propagation routing optimisation of product design change considering multi-domain network collaboration;Journal of Engineering Design;2024-02-27

2. Adaptive design change considering making small impact on the original manufacturing process;Advanced Engineering Informatics;2024-01

3. Digital twin and parameter correlation-enabled variant design of production lines;International Journal of Computer Integrated Manufacturing;2023-12-22

4. Data driven design optimisation: an empirical study of demand discovery combining theory of planned behaviour and Bayesian networks;International Journal of Production Research;2023-10-26

5. A Product-Design-Change-Based Recovery Control Algorithm for Supply Chain Disruption Problem;Electronics;2023-06-06