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.