Multi-factor integrated configuration model and three-layer hybrid optimization algorithm framework: turnkey project-oriented rapid manufacturing system configuration

doi:10.1007/s40436-023-00476-8

Advances in Manufacturing ›› 2024, Vol. 12 ›› Issue (4): 698-725.doi: 10.1007/s40436-023-00476-8

• • 上一篇

Multi-factor integrated configuration model and three-layer hybrid optimization algorithm framework: turnkey project-oriented rapid manufacturing system configuration

Shu-Lian Xie, Feng Xue, Wei-Min Zhang, Jia-Wei Zhu, Zi-Wei Jia

School of Mechanical Engineering, Tongji University, Shanghai, 201804, People's Republic of China

收稿日期:2023-04-09 修回日期:2023-07-17 发布日期:2024-12-06
通讯作者: Shu-Lian Xie,E-mail:shulian00@tongji.edu.cn E-mail:shulian00@tongji.edu.cn
作者简介:Shu-Lian Xie is a Ph.D. candidate of Mechanical Engineering at Tongji University, Shanghai, China. His current research interests include intelligent manufacturing systems and Industry 4.0-oriented turnkey projects. Feng Xue is currently a Ph.D. candidate of Mechanical Engineering in Tongji University, Shanghai, China. His current research interests include intelligent diagnostic and optimization technologies for machine components and feeding systems. Wei-Min Zhang received his Ph.D. degree in Theory of Mechanical Design from Tongji University, Shanghai, China, in 1999. He is a professor and head of the Institute of Advanced Manufacturing Technology in Tongji University. His current research interests include intelligent manufacturing, industry 5G technology, learning factory, and autonomous systems. Jia-Wei Zhu is currently a research assistant at Tongji University, Shanghai, China. He received his bachelor’s degree at Xi’an Jiaotong University, Xi’an, China. His current research interest includes advanced manufactur ing and machine learning. Zi-Wei Jia is a Ph.D. candidate of Mechanical Engineering at Tongji University, Shanghai, China. His current research interests include human-machine collaboration (HMC) and quality closed-loop control oriented to uncertainty.
基金资助:
This work was supported by the National Key Research & Development Program of China (Grant No. 2017YFE0101400, 2022YFE0114100).

Multi-factor integrated configuration model and three-layer hybrid optimization algorithm framework: turnkey project-oriented rapid manufacturing system configuration

Shu-Lian Xie, Feng Xue, Wei-Min Zhang, Jia-Wei Zhu, Zi-Wei Jia

School of Mechanical Engineering, Tongji University, Shanghai, 201804, People's Republic of China

Received:2023-04-09 Revised:2023-07-17 Published:2024-12-06
Contact: Shu-Lian Xie,E-mail:shulian00@tongji.edu.cn E-mail:shulian00@tongji.edu.cn
Supported by:
This work was supported by the National Key Research & Development Program of China (Grant No. 2017YFE0101400, 2022YFE0114100).

摘要/Abstract

摘要： In the context of increasingly prominent product personalization and customization trends, intelligent manufacturing-oriented turnkey projects can provide manufacturers with fast and convenient turnkey services for manufacturing systems. Their key characteristic is the transformation of the traditional design process into a configuration process. However, the scope of configuration resources in existing research is limited; the cost and time required for manufacturing system construction are overlooked; and the integration of the system layout configuration is rarely considered, making it difficult to meet the manufacturing system configuration requirements of turnkey projects. In response, this study establishes a multi-factor integrated rapid configuration model and proposes a solution method for manufacturing systems based on the requirements of turnkey projects. The configuration model considers the system construction cost and duration and the product manufacturing cost and duration, as optimization objectives. The differences in product feature-dividing schemes and configuration of processes, equipment, tools, fixtures, and layouts were considered simultaneously. The proposed model-solving method is a three-layer hybrid optimization algorithm framework with two optimization algorithm modules and an intermediate algorithm module. Four hybrid configuration algorithms are established based on non-dominated sorting genetic algorithm-III (NSGAIII), non-dominated sorting genetic algorithm-II (NSGAII), multi-objective simulated annealing (MOSA), multi-objective neighborhood search (MONS), and tabu search (TS). These algorithms are compared and validated through a hydraulic valve block production case, and the TS and NSGAIII (TS-NSGAIII) hybrid algorithm exhibits the best performance. This case demonstrates the effectiveness of the proposed model and solution method.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-023-00476-8

关键词: Manufacturing systems, Configuration, Turnkey projects, Hybrid optimization algorithm, Multi-objective optimization

Abstract: In the context of increasingly prominent product personalization and customization trends, intelligent manufacturing-oriented turnkey projects can provide manufacturers with fast and convenient turnkey services for manufacturing systems. Their key characteristic is the transformation of the traditional design process into a configuration process. However, the scope of configuration resources in existing research is limited; the cost and time required for manufacturing system construction are overlooked; and the integration of the system layout configuration is rarely considered, making it difficult to meet the manufacturing system configuration requirements of turnkey projects. In response, this study establishes a multi-factor integrated rapid configuration model and proposes a solution method for manufacturing systems based on the requirements of turnkey projects. The configuration model considers the system construction cost and duration and the product manufacturing cost and duration, as optimization objectives. The differences in product feature-dividing schemes and configuration of processes, equipment, tools, fixtures, and layouts were considered simultaneously. The proposed model-solving method is a three-layer hybrid optimization algorithm framework with two optimization algorithm modules and an intermediate algorithm module. Four hybrid configuration algorithms are established based on non-dominated sorting genetic algorithm-III (NSGAIII), non-dominated sorting genetic algorithm-II (NSGAII), multi-objective simulated annealing (MOSA), multi-objective neighborhood search (MONS), and tabu search (TS). These algorithms are compared and validated through a hydraulic valve block production case, and the TS and NSGAIII (TS-NSGAIII) hybrid algorithm exhibits the best performance. This case demonstrates the effectiveness of the proposed model and solution method.

The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-023-00476-8

Key words: Manufacturing systems, Configuration, Turnkey projects, Hybrid optimization algorithm, Multi-objective optimization

Shu-Lian Xie, Feng Xue, Wei-Min Zhang, Jia-Wei Zhu, Zi-Wei Jia. Multi-factor integrated configuration model and three-layer hybrid optimization algorithm framework: turnkey project-oriented rapid manufacturing system configuration[J]. Advances in Manufacturing, 2024, 12(4): 698-725.

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Multi-factor integrated configuration model and three-layer hybrid optimization algorithm framework: turnkey project-oriented rapid manufacturing system configuration

Multi-factor integrated configuration model and three-layer hybrid optimization algorithm framework: turnkey project-oriented rapid manufacturing system configuration

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