Research on joint scheduling method of order grading and machine maintenance

IF 2.5 Q2 ENGINEERING, INDUSTRIAL IET Collaborative Intelligent Manufacturing Pub Date : 2024-04-26 DOI:10.1049/cim2.12102
Wenyu Zeng, Mingfu Li, Ruisen Jiang, Ye Huang, Gaopan Lei, Yi Liu
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Abstract

In the multi-variety and large-scale order production mode, enterprises must balance delivery deadlines and maintain customer satisfaction while also considering the health status of machines. Therefore, the authors propose a method for jointly optimising production scheduling and machine maintenance. Before machine processing, an order value grading and sorting model and a machine health-status group partitioning model are constructed to classify orders into different production value levels and machines into different health-status groups, respectively. During machine processing, based on the Weibull distribution theory, a ‘health evaluation function value’ constraint machine preventive maintenance (PM) model and PM strategy are proposed to account for the changing health status of machines; these are integrated with the order allocation machine strategy as decision-making elements in the production schedule. Finally, two case studies are used to verify the effectiveness of this proposed model and method. The results show that compared to general scheduling schemes, the proposed method can reduce total delay and improve customer satisfaction. Additionally, the PM plan proposed in this method can improve production efficiency and line stability compared to periodic maintenance.

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订单分级和机器维护联合调度方法研究
在多品种、大规模订单生产模式下,企业必须平衡交货期限和保持客户满意度,同时还要考虑机器的健康状况。因此,作者提出了一种联合优化生产调度和机器维护的方法。在机器加工之前,构建了订单价值分级和排序模型以及机器健康状态组划分模型,分别将订单划分为不同的产值级别,将机器划分为不同的健康状态组。在机器加工过程中,基于威布尔分布理论,提出了 "健康评价函数值 "约束机器预防性维护(PM)模型和 PM 策略,以考虑机器健康状况的变化;这些模型和策略与订单分配机器策略相结合,成为生产计划的决策要素。最后,通过两个案例研究验证了所提模型和方法的有效性。结果表明,与一般排产方案相比,所提出的方法可以减少总延迟,提高客户满意度。此外,与定期维护相比,该方法提出的 PM 计划可以提高生产效率和生产线稳定性。
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来源期刊
IET Collaborative Intelligent Manufacturing
IET Collaborative Intelligent Manufacturing Engineering-Industrial and Manufacturing Engineering
CiteScore
9.10
自引率
2.40%
发文量
25
审稿时长
20 weeks
期刊介绍: IET Collaborative Intelligent Manufacturing is a Gold Open Access journal that focuses on the development of efficient and adaptive production and distribution systems. It aims to meet the ever-changing market demands by publishing original research on methodologies and techniques for the application of intelligence, data science, and emerging information and communication technologies in various aspects of manufacturing, such as design, modeling, simulation, planning, and optimization of products, processes, production, and assembly. The journal is indexed in COMPENDEX (Elsevier), Directory of Open Access Journals (DOAJ), Emerging Sources Citation Index (Clarivate Analytics), INSPEC (IET), SCOPUS (Elsevier) and Web of Science (Clarivate Analytics).
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