{"title":"多因素综合配置模型和三层混合优化算法框架:面向交钥匙工程的快速制造系统配置","authors":"Shu-Lian Xie, Feng Xue, Wei-Min Zhang, Jia-Wei Zhu, Zi-Wei Jia","doi":"10.1007/s40436-023-00476-8","DOIUrl":null,"url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":7342,"journal":{"name":"Advances in Manufacturing","volume":"12 4","pages":"698 - 725"},"PeriodicalIF":4.2000,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-factor integrated configuration model and three-layer hybrid optimization algorithm framework: turnkey project-oriented rapid manufacturing system configuration\",\"authors\":\"Shu-Lian Xie, Feng Xue, Wei-Min Zhang, Jia-Wei Zhu, Zi-Wei Jia\",\"doi\":\"10.1007/s40436-023-00476-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>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.</p></div>\",\"PeriodicalId\":7342,\"journal\":{\"name\":\"Advances in Manufacturing\",\"volume\":\"12 4\",\"pages\":\"698 - 725\"},\"PeriodicalIF\":4.2000,\"publicationDate\":\"2024-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Manufacturing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s40436-023-00476-8\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, MANUFACTURING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Manufacturing","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s40436-023-00476-8","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
Multi-factor integrated configuration model and three-layer hybrid optimization algorithm framework: turnkey project-oriented rapid manufacturing system configuration
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.
期刊介绍:
As an innovative, fundamental and scientific journal, Advances in Manufacturing aims to describe the latest regional and global research results and forefront developments in advanced manufacturing field. As such, it serves as an international platform for academic exchange between experts, scholars and researchers in this field.
All articles in Advances in Manufacturing are peer reviewed. Respected scholars from the fields of advanced manufacturing fields will be invited to write some comments. We also encourage and give priority to research papers that have made major breakthroughs or innovations in the fundamental theory. The targeted fields include: manufacturing automation, mechatronics and robotics, precision manufacturing and control, micro-nano-manufacturing, green manufacturing, design in manufacturing, metallic and nonmetallic materials in manufacturing, metallurgical process, etc. The forms of articles include (but not limited to): academic articles, research reports, and general reviews.