OPPA

OPTIMEX-PUMP PREDICT-ADAPT

“IoT electrical signature analysis for canned motor pumps”

There are billions of electric motors worldwide, 300 million of which are critical to the safety, production or service continuity of their owners/operators/users. A significant share is used to power pumps. However, they incur an average of 180h of unexpected downtime per year that lead to lost productivity, high maintenance and repair costs, or even critical safety and environmental issues (e.g. chemical spill, unavailable firefighting water pumps).

After the warranty period, up to 80% of pump failures occur due to rolling element bearings, seal failure or electrical unbalance causing heat and lubricant degradation. Industrial companies have usually dealt with this issue either by:

• Running costly preventative maintenance programs and/or specifying monitoring systems (often relying on vibratory analysis)
• Specifying, when possible, more reliable canned motor pumps, that use plain bearings and are hermetically sealed.

The OPPA project aims at applying the next generation of IoT predictive maintenance technology (electrical signature analysis) to the most advanced and reliable pump design currently available (canned motor pumps) and explore the opportunity to launch a solution able to:

• Act as a monitoring system in normal operating condition,
• Warn the operator ahead of any type of critical event so that it can react in time.

If successful, and once combined into a single offering, this has the potential to redefine the state-of-the-art in terms of reliability and monitoring for industrial pumping applications.

About the two companies:

Since 2015, ECO-ADAPT has been developing Predict-Adapt, an electrical analysis solution that has already been developed, tested and deployed on numerous machines on bench and in operating conditions.

OPTIMEX is a canned motor pump designer and manufacturer in activity since 1998 with more than 800 references. Its pumps are already well proven systems on the market.

Vertical sector addressed

• Energy & utilities

Industrial application addressed

• Predictive maintenance
• Monitoring & control

Technologies involved

• IoT
• Big Data & AI