Proposed Procedure for Optimal Maintenance Scheduling Under Emergent Failures

Abstract

Production lines are usually subjected to emergent machine failures. Such emergent failures disrupt pre-established maintenance schedules, which challenge maintenance engineers to react to those failures in real time. This research proposes an optimization procedure for optimizing scheduling repairs of emergent failures. Three optimization models are developed. Model I schedules failures in newly idle repair shops with the objective of maximizing the number of scheduled repairs. Model II maximizes the number of assigned repairs to untapped ranges. Model III maximizes both the number of assigned failure repairs and satisfaction on regular and emergency repairs by resequencing regular and emergent failures in the shop that contains the largest free margin. A real case study is provided to illustrate the proposed optimization procedure. Results reveal that the proposed models efficiently scheduled and sequenced emergent failures in the idle maintenance shops, the untapped ranges between repairs of regular failures, and in the maintenance shop with the largest free margin. In conclusions, the proposed models can greatly support maintenance engineers in planning repairs under unexpected failures.

Systematic literature review of repair shops: focus on sustainability

“…[t]Table 5 near here [/t] Considering the optimization of the performance indicators of the repair shops, it could be observed that Linear or Non-linear Programming (16 papers) are the algorithms most commonly used, accounting for 30% of all papers. The objective is to minimize either the expected waiting time in repair shops (Safaei et al 2011;Liang et al 2013;Aramon and Beck 2014;Dreyfuss et al 2018;Al-Refaie et al 2020;Driessen et al 2020) or the spare parts inventory (Adan et al 2009;Basten and van Houtum 2014;Jaber et al 2014;van Jaarsveld et al 2015;Taleizadeh et al 2016;Arts 2017;Sleptchenko et al 2019) or the maintenance costs (van Ommeren et al 2006;Simeu-Abazi and Ahmad 2011;Shivasankaran et al 2013;Turan et al 2018;Sanchez et al 2020). The advantage of both methods is that they are exact, even though the repair shop model needs to be simplified as much as possible to reduce calculation complexity.…”

“…More basically defined, repair shop capacity is a set of centralized facilities for maintenance in the optimum location (Simeu-Abazi et al 2014). Centralization mainly considers scheduling and policies such as maintenance activity scheduling, scheduling under emergent failures, priority policies, and overtime policies (increased repair capacity as needed to offset short-term demand fluctuations) (Scudder and Chua 1987;Al-Refaie et al 2020). Furthermore, a repair shop capacity could be simplified and modeled as a single server, considered finite or infinite depending on the facilities (Sleptchenko et al 2002).…”

Analysis of the Impact of Input Data on the Planned Costs of Building Maintenance

“…Peach and Visser [19] analyze the problem of including human factors in maintenance. Much of the articles are devoted to the proper planning schedule repairs [20][21][22].…”