Abstract
This research paper explores the impact of AI-powered predictive maintenance on industrial equipment. Predictive maintenance is crucial for minimizing downtime and optimizing asset performance. AI has made maintenance more proactive, efficient, and cost-effective. The paper reviews maintenance practices, the evolution of predictive techniques, and AI integration. Through literature review and case studies, it examines efficacy, challenges, and implications of AI-powered maintenance. Findings highlight benefits such as enhanced efficiency, cost reduction, and extended equipment lifespan. Challenges include data quality, model accuracy, and organizational readiness. The paper concludes with recommendations for practitioners and policymakers, emphasizing AI's potential to revolutionize maintenance and foster a sustainable future. Keywords: Predictive maintenance, AI-powered maintenance, Industrial equipment, Maintenance efficiency, Asset performance optimization, Data quality
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