AI And CMMS: A Powerful Duo For Enhanced Maintenance In Manufacturing

Abstract

The paper investigated the integration of Artificial Intelligence (AI) with Computerized Maintenance Management Systems (CMMS) in manufacturing industries to enhance maintenance performance. By leveraging AI algorithms, including machine learning and predictive analytics, CMMS can predict equipment failures, optimize maintenance schedules, and automate asset management processes. The study is descriptive and conducted with the help of secondary data. Research papers, books, journals, newspapers, and continuing academic working papers are the sources of secondary data. This proactive approach minimizes downtime, reduces operational costs, and extends asset lifespan. The literature review highlights key themes such as AI's impact on maintenance performance metrics and the limitations of current technologies. Despite benefits, challenges like high implementation costs and workforce displacement concerns exist. The study concludes that AI-enhanced CMMS streamlines maintenance work-flows, improves decision-making, and enhances overall equipment effectiveness. Future research opportunities include refining AI algorithms, optimizing technology integration, and exploring sustainability impacts. This research contributes to understanding the transformative potential of AI in manufacturing maintenance.