Unexpected failure or performance erosion of production equipment can significantly impact productivity, product quality and maintenance expenses within any manufacturing organization. It’s also difficult to get operations ‘back on track’ after these failures occur. The good news is that, via the Internet of Things, intelligent use of sensor data, machine learning and optimization can help companies take a proactive approach to predicting failures and re-optimizing processes around them. This Q&A with Dr. Michael Watson, Partner at Opex Analytics and Adjunct Professor at Northwestern University, discusses: The evolution of sensors in manufacturing plants, and their increased use as costs decrease How some manufacturers are getting more creative with sensor data – evolving from predictive to prescriptive (optimization) analytics to drive better actions How an optimization-powered approach can help you not only better predict failure, but also determine what to fix today vs. later (or not at all)
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