Joint OnPoint Session between ISA Montreal and ChemPID Division<\/p>\n
Presenters:\u00a0<\/strong><\/p>\n Abstract:<\/strong><\/p>\n In today’s fast-paced and ever-changing industrial environment, minimizing operating costs and maximizing yield are critical to success. \u00a0When plant equipment goes down due to a failure, both key performance indicators are impacted.\u00a0 \u00a0Maintenance teams regularly rely on mature maintenance techniques that focus on scheduled maintenance planning and periodic equipment inspection to keep equipment running.<\/p>\n \u00a0One of the most common industrial devices are AC induction motors which are frequently controlled by variable frequency drives (VFD).\u00a0 As VFD\u2019s become increasingly intelligent and AI technology evolves. new maintenance techniques have emerged to predict failures prior to their occurrence.<\/p>\n \u00a0Today\u2019s topic will explore the concepts of motor current signature analysis (MCSA) and how AI can interpret it.\u00a0 Using a machine learning based supervisory application, we can establish a baseline of each asset\u2019s behavior under normal operating conditions.\u00a0 Then, it monitors the assets for any deviation from baseline.\u00a0 Once a deviation is detected, a notification can be sent to maintenance which can include the anomalies first principle faults like: angular misalignment, bearing fault, flow restrictions, cavitation and others depending on the application.<\/p>\n\n