The Maintenance Management

Author:

Pelantová Věra

Abstract

The chapter deals with the maintenance management. The review is based on maintenance and management trends in organisations in 2022 and on other findings. There are also historical parallels. Aspects such as maintenance planning and control and management including downtime, resources in terms as material (spare parts and added materials) and personnel are discussed. The issue is linked to other management systems such as quality control, occupational safety, and environment and information security. The methods of planning and control of equipment maintenance are presented. The application of the process approach and the concept of maintenance as a process that needs to be improved are described. The relationship to the Industry 4.0 is mentioned. Linking to risk management is included in this chapter. The chapter is based on a small survey probe in several organisations, and points out identified nonconformities of the maintenance and suggested actions. The goal is effective maintenance for needs of organisations in a current dynamic environment.

Publisher

IntechOpen

Reference46 articles.

1. Koch S et al. Tackling problems on maintenance and evolution in industry 4.0 scenarios using a distributed architecture. In: Götz S, Linsbauer L, Schaefer I, Wortmann A, editors. Software Engineering. Satellite Events, Lecture Notes in Informatics (LNI). Vol. 2814. Bonn: Gesellschaft für Informatic; 2021. Available from: http://www.ceur-ws.org/Vol-2814/short-A5-4.pdf

2. Qin W et al. Sustainable service-oriented equipment maintenance management of steel enterprises using a two-stage optimization approach. Robotics and Computer-Integrated Manufacturing. 2022;75:102311. DOI: 10.1016/j.rcim.2021.102311. Available from: https://www.sciencedirect.com/science/article/pii/S0736584521001915

3. Martínez-Galán Fernández P et al. Dynamic risk assessment for CBM-based adaptation of maintenance planning. Reliability Engineering & System Safety. 2022;223:108359. DOI: 10.1016/j.ress.2022.108359. Available from: https://www.sciencedirect.com/science/article/abs/pii/S0951832022000382?casa_token=pEqh_ZVFPLYAAAAA:VugVfoGHDrmaEa5eSG4bUnF61XR6wz3r7EbHMC4IHrfMz63DtWAAW65WpZasdClVMkvCVr77yg

4. Gopalakrishnan M et al. Data-driven machine criticality assessment – Maintenance decision support for increased productivity. Production Planning and Control, The Management of Operations. 2022;33(1):1-19. DOI: 10.1080/09537287.2022.1817601. Available from: https://www.tandfonline.com/doi/full/10.1080/09537287.2020.1817601

5. Dolorme M et al. Solution methods for scheduling problems with sequence-dependent deterioration and maintenance events. European Journal of Operational Research. 2021;295(3):823-837. DOI: 10.1016/j.ejor.2021.03.067. Available from: https://www.sciencedirect.com/science/article/pii/S0377221721003726

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3