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Equipment Reliability Optimization Using Predictive Reliability Centered Maintenance

Authors :
Kimuel Kier Mercado Rosita
Maria Victorina Dalistan Rada
Source :
2021 IEEE 8th International Conference on Industrial Engineering and Applications (ICIEA).
Publication Year :
2021
Publisher :
IEEE, 2021.

Abstract

Extending the work of (Prasetyo &Rosita, 2020) in this study, the application of Reliability Centered Maintenance (RCM) to optimize equipment reliability is presented through a framework developed for ABC manufacturing company. ABC company is a well-established manufacturing company in the middle east that already has their current maintenance strategy to maximize their equipment reliability but based on the data collected from SAP on where they stored their historical data from maintenance and operation, their MTBF is low and their MTTR is quite high. This is because of their high machine downtime hours and repeated failures. Reliability Centered Maintenance (RCM) integrates Preventive Maintenance (Interval-based), Reactive Maintenance, Proactive Maintenance and Condition Based Maintenance to increase the machines performance and the component will function in the required manner over its design life-cycle with a very less amount of machine downtime and parts failure. To implement RCM in ABC manufacturing company and apply the developed framework, the failure modes collected from SAP was analyzed using Failure Mode and Effect Analysis (FMEA) with the help of RCM Logic tree analysis for decision making and establishing maintenance criticality criteria. The last part of this paper shows the possible maintenance selection task for each failure modes that the company can consider, challenges in implementing RCM are also explained which might influence the plan of adopting the RCM process in an already established organization. It is also worth mentioning that the developed framework can be apply also in different manufacturing industries that want to implement Reliability Centered Maintenance (RCM).

Details

Database :
OpenAIRE
Journal :
2021 IEEE 8th International Conference on Industrial Engineering and Applications (ICIEA)
Accession number :
edsair.doi...........0ad749eef00f65d03d282db3119520a3
Full Text :
https://doi.org/10.1109/iciea52957.2021.9436745