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A Systematic Review of Predictive Maintenance and Production Scheduling Methodologies with PRISMA Approach


Salma Maataoui, Ghita Bencheikh, and Ghizlane Bencheikh


Vol. 24  No. 1  pp. 215-225


Predictive maintenance has been considered fundamental in the industrial applications in the last few years. It contributes to improve reliability, availability, and maintainability of the systems and to avoid breakdowns. These breakdowns could potentially lead to system shutdowns and to decrease the production efficiency of the manufacturing plants. The present article aims to study how predictive maintenance could be planed into the production scheduling, through a systematic review of literature. The review includes the research articles published in international journals indexed in the Scopus database. 165 research articles were included in the search using predictive maintenance AND production scheduling. Press articles, conference and non-English papers are not considered in this study. After careful evaluation of each study for its purpose and scope, 50 research articles are selected for this review by following the 2020 Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA) statement. A benchmarking of predictive maintenance methods was used to understand the parameters that contributed to improve the production scheduling. The results of the comparative analysis highlight that artificial intelligence is a promising tool to anticipate breakdowns. An additional impression of this study is that each equipment has its own parameters that have to be collected, monitored and analyzed.


Predictive maintenance; production scheduling; systematic review; PRISMA.