IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Mathematical Optimization Models for the Maintenance Policies in Production Systems

Mathematical Optimization Models for the Maintenance Policies in Production Systems
View Sample PDF
Author(s): Alperen Bal (Istanbul Technical University, Turkey)and Sule Itir Satoglu (Istanbul Technical University, Turkey)
Copyright: 2018
Pages: 17
Source title: Handbook of Research on Applied Optimization Methodologies in Manufacturing Systems
Source Author(s)/Editor(s): Ömer Faruk Yılmaz (Istanbul Technical University, Turkey & Yalova University, Turkey)and Süleyman Tüfekçí (University of Florida, USA)
DOI: 10.4018/978-1-5225-2944-6.ch012

Purchase

View Mathematical Optimization Models for the Maintenance Policies in Production Systems on the publisher's website for pricing and purchasing information.

Abstract

This chapter initially presents a brief information about production systems. At these systems, different types of maintenance policies are developed to cope with wear out failures. Mainly used maintenance policies can be classified as corrective, preventive, and condition-based maintenance. In the corrective maintenance, repair or replacement is applied whenever components of the machine breakdown. In the preventive maintenance approach maintenance activities are applied to the critical components on a periodic basis. On the other hand, maintenance activities are applied whenever critical reliability level is reached or exceeded. These types of maintenance policies are modeled using mathematical modeling techniques such as linear programming, goal programming, dynamic programming, and simulation. A review of current literature about the mathematical models, the simulation-based optimization studies examining these maintenance policies are categorized and explained. Besides, the solution methodologies are discussed. Finally, the opportunities for future research are presented.

Related Content

Poshan Yu, Zixuan Zhao, Emanuela Hanes. © 2023. 29 pages.
Subramaniam Meenakshi Sundaram, Tejaswini R. Murgod, Madhu M. Nayak, Usha Rani Janardhan, Usha Obalanarasimhaiah. © 2023. 20 pages.
Rekha R. Nair, Tina Babu, Kishore S.. © 2023. 23 pages.
Wasswa Shafik. © 2023. 22 pages.
Jay Kumar Jain, Dipti Chauhan. © 2023. 24 pages.
George Makropoulos, Dimitrios Fragkos, Harilaos Koumaras, Nancy Alonistioti, Alexandros Kaloxylos, Vaios Koumaras, Theoni Dounia, Christos Sakkas, Dimitris Tsolkas. © 2023. 19 pages.
Shouvik Sanyal, Kalimuthu M., Thangaraja Arumugam, Aruna R., Balaji J., Ajitha Savarimuthu, Chandan Chavadi, Dhanabalan Thangam, Sendhilkumar Manoharan, Shasikala Patil. © 2023. 17 pages.
Body Bottom