Re-Entrant Green Scheduling Problem of Bearing Production Shops Considering Job Reworking

Machines Pub Date : 2024-04-22 DOI:10.3390/machines12040281
Yansen Wang, Jianwei Shi, Wenjie Wang, Cheng Li
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Abstract

To solve various reworking and repair problems caused by unqualified bearing product quality inspections, this paper introduces a green re-entrant scheduling optimization method for bearing production shops considering job reworking. By taking into account quality inspection constraints, this paper establishes an integrated scheduling mathematical model based on the entire processing–transportation–assembly process of bearing production shops with the goals for minimizing the makespan, total carbon emissions, and waste emissions. To solve these problems, the concepts of the set of the longest common machine routes (SLCMR) and the set of the shortest recombination machine combinations (SSRMC) were used to propose the re-entrant scheduling optimization method, based on system reconfiguration, to enhance the system stability and production scheduling efficiency. Then, a multi-objective hybrid optimization algorithm, based on a neighborhood local search (MOOA-LS), is proposed to improve the search scope and optimization ability by constructing a multi-level neighborhood search structure. Finally, this paper takes a bearing production shop as an example to carry out the case study and designs a series of experimental analyses and comparative tests. The final results show that in the bearing production process, the proposed model and algorithm can effectively realize green and energy-saving re-entrant manufacturing scheduling.
考虑作业返工的轴承生产车间再进入绿色排产问题
为解决轴承产品质量检验不合格引起的各种返工和修理问题,本文介绍了一种考虑作业返工的轴承生产车间绿色重入排程优化方法。考虑到质量检验约束,本文建立了基于轴承生产车间整个加工-运输-装配过程的综合排产数学模型,目标是最小化生产周期、总碳排放量和废物排放量。为解决这些问题,利用最长共同机器路线集(SLCMR)和最短重组机器组合集(SSRMC)的概念,提出了基于系统重构的重入排程优化方法,以提高系统稳定性和生产排程效率。然后,提出了基于邻域局部搜索的多目标混合优化算法(MOOA-LS),通过构建多级邻域搜索结构,提高了搜索范围和优化能力。最后,本文以轴承生产车间为例进行了案例研究,并设计了一系列实验分析和对比测试。最终结果表明,在轴承生产过程中,本文提出的模型和算法能有效实现绿色节能的重入式生产排程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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