Artificial Intelligence-based Fault Diagnosis Procedure for a Sustainable Manufacturing Industry

Abstract All industries are fast transforming into smart as part of the sustainable developments in fourth industrial revolution. Predictive maintenance is one most important aspects such industries, to avoid unanticipated machine breakdowns and catastrophic failures. Machine vibration analysis a common tool for predicting state machinery. Vibration involves analysing data collected from machinery determining whether or not fault exists. Despite fact that different methods utilized handle data, artificial intelligence capable processing without need human intervention. Every day, substantial amount study carried out this field. New strategies, on other hand, yield greater classification accuracy have yet be developed. With use approaches, research article attempts offer an effective defect detection method rolling element bearings. To illustrate practical applications, technique used real datasets which were developed by Case Western Reserve University, regarded gold standard testing diagnostic algorithms.