Manufacturing 4.0: AI-Driven Analytics for Predictive Maintenance

Author(s)	Gautam Ulhas Parab
Country	United States
Abstract	Integrating artificial intelligence and advanced analytics in manufacturing has revolutionized traditional maintenance approaches, particularly through implementing predictive maintenance systems. This comprehensive article explores the transformation of manufacturing operations through AI-driven technologies, examining their impact on operational efficiency, cost reduction, and strategic advantages. The article investigates various aspects, including implementation strategies, challenges, and solutions across manufacturing sectors. Key focus areas include production line optimization, quality control integration, and supply chain management, demonstrating how predictive maintenance improves equipment reliability, reduces downtime, and enhances operational performance. The article also examines the financial implications and strategic benefits of these implementations while addressing both technical and organizational challenges faced by manufacturing facilities during adoption.
Keywords	AI-Driven Predictive Maintenance, Smart Manufacturing, Industry 4.0, Equipment Effectiveness, Manufacturing Analytics
Field	Computer
Published In	Volume 6, Issue 6, November-December 2024
Published On	2024-12-22
DOI	https://doi.org/10.36948/ijfmr.2024.v06i06.33539
Short DOI	https://doi.org/g8w2zt

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International Journal For Multidisciplinary Research