Modeling and solving framework for tactical maintenance planning problems with health index considerations

IF 4.1 2区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Ernest Foussard , Margaux Nattaf , Marie-Laure Espinouse , Grégory Mounié
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引用次数: 0

Abstract

Maintenance planning is one of the main challenges of the management of production systems. Thanks to recent technological innovations and the development of sensors, it is possible to construct degradation models of equipment condition, thus providing an assessment of the equipment health modeled by a health index indicator. In this work, we present an original tactical maintenance planning problem involving a Health Index indicator on the components of the equipment. Within this framework, maintenance can be seen as a form of delayed production. This observation allows us to derive an original lot-sizing based approach for our tactical maintenance planning problem. Aside from the classical cost minimization objective, the problem also involves a resource consumption objective to be minimized. The problem is proven to be strongly NP-hard in the general case, and a bi-objective Mixed Integer Linear Program is proposed. Then, two matheuristics are defined. A degradation matheuristic allowing several degradations of the objective functions and a Pareto-based matheuristic selecting solution of good quality from a restricted pareto front.

考虑健康指数的战术维护规划问题建模与求解框架
维护计划是生产系统管理的主要挑战之一。得益于最近的技术创新和传感器的发展,我们有可能构建设备状态退化模型,从而提供以健康指数指标为模型的设备健康评估。在这项工作中,我们提出了一个新颖的战术维护计划问题,涉及设备组件的健康指数指标。在此框架内,维护可以被视为一种延迟生产的形式。基于这一观点,我们为战术维护计划问题提出了一种基于批量大小的原创方法。除了传统的成本最小化目标外,该问题还涉及资源消耗最小化目标。在一般情况下,该问题被证明为强 NP 难,并提出了一个双目标混合整数线性规划。然后,定义了两种矩阵。一种是允许对目标函数进行多种降级的降级矩阵,另一种是基于帕累托的矩阵,从受限的帕累托前沿选择高质量的解决方案。
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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来源期刊
Computers & Operations Research
Computers & Operations Research 工程技术-工程:工业
CiteScore
8.60
自引率
8.70%
发文量
292
审稿时长
8.5 months
期刊介绍: Operations research and computers meet in a large number of scientific fields, many of which are of vital current concern to our troubled society. These include, among others, ecology, transportation, safety, reliability, urban planning, economics, inventory control, investment strategy and logistics (including reverse logistics). Computers & Operations Research provides an international forum for the application of computers and operations research techniques to problems in these and related fields.
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