SMART FAULT DIAGNOSTICS: AI-POWERED PRECISION FOR NEXT-GEN MANUFACTURING
Keywords:
accuracy, anomaly detection, deep learning, fault classification, machine learning, predictive maintenance, reliabilityAbstract
Mechanical failures in industrial machinery can cause costly disruptions, increase maintenance expenses, and pose serious safety risks. As industries prioritize early fault detection, the global market for predictive maintenance technologies surpassed $10 billion in 2023. Accurate fault classification is key to keeping equipment reliable and preventing downtime. Traditional diagnosis methods, like
manual inspections and heuristic analysis, are time-consuming, require expert knowledge, and often fail to catch early signs of failure.
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