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A large number of the presentations at ARC Advisory Group's recent Industry Forum in Orlando, Florida, focused on how Industrial Internet of Things (IIoT) technologies, such as smart sensors, predictive analytics, and machine learning, can be applied to improve the availability, reliability, and performance of industrial assets and enable new business models.
In one presentation, Rob Miller, General Manager, Global Solutions for Flowserve, discussed how the company plans a step change in maintenance and reliability practices for its customers by integrating advanced machine learning capabilities. Flowserve has been evaluating the potential of machine learning to improve its equipment monitoring capabilities for the past twenty years, but – until recently – these had proven too costly and difficult to commercialize.
As Mr. Miller explained, Flowserve's initial approach involved increasing data acquisition capabilities utilizing wireless technologies to bring pump health data up to the plant-, or cloud-level and eventually migrate to actively monitoring its customers' equipment. However, with this approach, the company faced many challenges in predicting equipment failures with adequate advanced notice to allow its customers to react effectively to alerts.
Recent advancements in data science technology and computing power have enabled the company to refine its methodology enabling it to introduce a step change in its equipment monitoring capabilities. Integrating machine learning techniques and cognitive analytics have enabled Flowserve to provide more advanced warning of impending pump failure, enabling customers adequate time to remediate the problem prior to failure to avoid costly unplanned downtime.
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Keywords: ARC Industry Forum, Pumps, Predictive Maintenance, Reliability, Ma-chine Learning, Cognitive Analytics, Artificial Intelligence, Security, IIoT, ARC Advisory Group.