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

IF 4.2 2区 工程技术 Q2 ENGINEERING, MANUFACTURING
Shu-Lian Xie, Feng Xue, Wei-Min Zhang, Jia-Wei Zhu, Zi-Wei Jia
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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.

Abstract Image

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
在产品个性化和定制化趋势日益突出的背景下,以智能制造为导向的交钥匙工程可以为制造商提供快速、便捷的制造系统交钥匙服务。其主要特点是将传统的设计过程转变为配置过程。然而,现有研究中配置资源的范围有限,忽视了制造系统构建所需的成本和时间,也很少考虑系统布局配置的集成,难以满足交钥匙工程对制造系统配置的要求。为此,本研究根据交钥匙工程的要求,建立了多因素集成快速配置模型,并提出了制造系统的解决方法。该配置模型将系统建设成本和工期以及产品制造成本和工期作为优化目标。同时考虑了产品特征划分方案以及工艺、设备、工具、夹具和布局配置的差异。所提出的模型求解方法是一个三层混合优化算法框架,包含两个优化算法模块和一个中间算法模块。基于非优势排序遗传算法-III(NSGAIII)、非优势排序遗传算法-II(NSGAII)、多目标模拟退火(MOSA)、多目标邻域搜索(MONS)和塔布搜索(TS)建立了四种混合配置算法。通过一个液压阀块生产案例对这些算法进行了比较和验证,其中 TS 和 NSGAIII(TS-NSGAIII)混合算法表现最佳。该案例证明了所提模型和求解方法的有效性。
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来源期刊
Advances in Manufacturing
Advances in Manufacturing Materials Science-Polymers and Plastics
CiteScore
9.10
自引率
3.80%
发文量
274
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.
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