Abstract

This research investigates the role of predictive maintenance (PdM) in enhancing operational excellence, addressing the challenges organizations face in effectively integrating this advanced maintenance strategy. The study highlights that PdM enables proactive interventions by utilizing real-time monitoring and advanced analytics to anticipate equipment failures, which helps optimize maintenance schedules and improve equipment reliability. It identifies significant challenges, such as high implementation costs and system integration complexities, that hinder organizations from adopting PdM fully. The research aims to provide actionable strategies to enhance the integration of predictive maintenance with other operational excellence practices while examining its impact on key performance metrics like Mean Time Between Failures (MTBF) and Overall Equipment Effectiveness (OEE). By collecting data through literature reviews and industry insights, this study seeks to bridge the knowledge gap surrounding PdM and its implications for operational efficiency, ultimately offering recommendations to guide organizations toward successful implementation and sustainable growth in a competitive business landscape. The results indicate that predictive maintenance has statistically significant positive effects on operational excellence, especially when it comes to equipment reliability, mean time between failures (MTBF), and reduction of unplanned downtime. The respondents indicated a high level of concurrence on the importance of predictive maintenance in promoting decision-making, resource management, and general effectiveness of equipment. Irrespective of demographic constraints, the findings also make predictive maintenance a crucial engine of operational performance and cost-efficiency.

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