Prescriptive Maintenance in the Digitized World

Published: 23 Jan 2018

Global pump manufacturers are focused on the manufacture of energy-efficient pumps. Energy cost accounts for 45% of the total lifecycle cost of a pump. However, manufacturers and end users are equally challenged by maintenance and downtime cost, which accounts for 25-30% of the total lifecycle cost. Pump maintenance has evolved from time and condition-based maintenance to predictive maintenance. Predictive maintenance captures the data generated by equipment sensors, facilitates data communication between devices through Internet-based connectivity, uses algorithms to identify anomalies in operation, and predicts asset failure. It has also been able to reduce maintenance and downtime by identifying expected failures, breakdowns, and other operational risks. However, it is limited to only finding the expected anomalies and fails to provide solutions for the same. With the advent of the Industrial Internet of Things (IIoT), pump manufacturers will be able to employ IIoT technologies such as cognitive machine learning, cloud computing, and real-time data analytics to improve the lifespan of pumps, which offers an opportunity for a new efficient maintenance process known as prescriptive maintenance.

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