{"title":"Joint maintenance and spare-parts inventory models: a review and discussion of practical stock-keeping rules","authors":"Phil Scarf, Aris Syntetos, Ruud Teunter","doi":"10.1093/imaman/dpad020","DOIUrl":null,"url":null,"abstract":"Abstract It is natural to coordinate spare-parts inventory planning and maintenance. However, work in the former area often neglects part utilisation, and work in the latter the fact that effective execution of maintenance schedules is conditioned to the availability of the necessary spare parts. This paper is a call for further integration between the two areas, and to that end we review the literature on mathematical modelling and analysis of inventory-maintenance-planning. We are not the first to address this issue (though we take a fresh perspective to the problem), but we are the first to complement such review with a discussion of simple stock keeping rules that may be used effectively in practice. We identify a growing gap between modelling and application, between theory and practice, that justifies the presentation of these simple stock keeping rules for the joint planning of inventory and maintenance. Thus, our work should be of interest not only to researchers who are looking for promising avenues for future research, but also to practitioners who are seeking to improve inventory-maintenance operations.","PeriodicalId":56296,"journal":{"name":"IMA Journal of Management Mathematics","volume":"57 1","pages":"0"},"PeriodicalIF":1.9000,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IMA Journal of Management Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/imaman/dpad020","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract It is natural to coordinate spare-parts inventory planning and maintenance. However, work in the former area often neglects part utilisation, and work in the latter the fact that effective execution of maintenance schedules is conditioned to the availability of the necessary spare parts. This paper is a call for further integration between the two areas, and to that end we review the literature on mathematical modelling and analysis of inventory-maintenance-planning. We are not the first to address this issue (though we take a fresh perspective to the problem), but we are the first to complement such review with a discussion of simple stock keeping rules that may be used effectively in practice. We identify a growing gap between modelling and application, between theory and practice, that justifies the presentation of these simple stock keeping rules for the joint planning of inventory and maintenance. Thus, our work should be of interest not only to researchers who are looking for promising avenues for future research, but also to practitioners who are seeking to improve inventory-maintenance operations.
期刊介绍:
The mission of this quarterly journal is to publish mathematical research of the highest quality, impact and relevance that can be directly utilised or have demonstrable potential to be employed by managers in profit, not-for-profit, third party and governmental/public organisations to improve their practices. Thus the research must be quantitative and of the highest quality if it is to be published in the journal. Furthermore, the outcome of the research must be ultimately useful for managers. The journal also publishes novel meta-analyses of the literature, reviews of the "state-of-the art" in a manner that provides new insight, and genuine applications of mathematics to real-world problems in the form of case studies. The journal welcomes papers dealing with topics in Operational Research and Management Science, Operations Management, Decision Sciences, Transportation Science, Marketing Science, Analytics, and Financial and Risk Modelling.