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In this 2-post blog series, we will be discussing the newest condition-based monitoring technology for rotating equipment. First, I want to talk about the urgent need for industrial businesses to find a better solution than traditional motor monitoring solutions. My next post will look in detail at how motor current signature analysis (MCSA) is answering this need.
Reducing Costly Downtime: An Industry-Wide Challenge
It has been reported that, on average, downtime costs for industry are around €25k to €40k ($29k to $47k) per hour. However, for some industries like automotive manufacturing, this can be as high as €42k ($50k) per minute! These costs relate to revenue losses, recovery costs and, in some cases, penalties and fines based on service level agreements or regulations.
Electric motors failures are a common cause of unplanned downtime. Rotating machinery driven by low or medium voltage AC induction motors represent the majority of industrial applications, from oil and gas, to mining, marine, airports, and logistical centers. Beyond motors, rotating equipment can include pumps, compressors, conveyors, blowers or fans, rolls or mills, etc.
With 20 to 25 percent of electric motors being critical to operations, and a typical annual failure rate of up to 7 percent, motors are having a large impact on downtime and losses. In addition, any needed repairs are often done during operating hours, causing further downtime. The U.S. Department of Energy Office of Industrial Technologies estimates that motors represent 60 percent of electrical energy consumption in manufacturing industries, and up to 90 percent in electro-intensive industries. Therefore, finding ways to improve efficiency can make a big difference to a company’s bottom line.
For these reasons, organizations need to begin moving to a more predictive maintenance strategy, to help avoid unscheduled repairs and downtime, and to improve efficiency, reduce costs, and extract longer lifespans from rotating equipment. Doing so requires the support of condition-based monitoring and predictive analytics.
Predictive Maintenance versus Traditional Motor Maintenance
A variety of maintenance strategies are used in the industrial environment. If a facility team uses ‘run-to-failure’ method, essentially minimal or no maintenance is performed on a motor until it fails completely. Obviously, the organization then must accept unplanned downtime as being part of its regular operations. If a preventative strategy is used, maintenance is done at set intervals – by calendar or running hours – with the aim to achieve a level of availability based on mean-time-between-failure statistics. Unfortunately, this means maintenance is often performed either too late, following a costly failure, or too early, potentially incurring unnecessary operational expenditures. And, ultimately, none of these strategies consider the actual condition of the motor.
A far better approach is predictive maintenance, with work performed only when the motor needs it, i.e. when performance is degrading or a fault is predicted. However, this approach requires that motor condition be monitored continuously. Optimally, the technology needs to detect risks at an early stage. Just a few examples of risk conditions include: bearing degradation, rotor or coupling eccentricities, mechanical unbalance, stator winding looseness, pump cavitation, harmonics disturbance, or axis misalignment. It is important to detect these types of risks early to reduce potential damage, minimize wasted energy and, most importantly, minimize unplanned downtime.
Problems with Traditional Motor Monitoring Technology
A variety of methods have been used to monitor motor conditions, some dating back many decades. Each has its strengths, but most have significant weaknesses.
For example:
- Vibration sensors can be thrown off by noise or vibrations from the surrounding environment
- Oil analysis and vibration analysis are not able to spot electrical problems
- Acoustic sensors are sensitive to background noise and interference from other objects
- Thermal cameras require a direct line of sight to the objects of interest and are sensitive to ambient temperature and the thermo-optical properties of the objects being monitored
For all of the technologies above, sensors must be placed on or near the asset to be monitored, which means they are not usable for motors in inaccessible places, such as those used for underground drainage, submersed in the hull of a ship, or encased within larger machines. They are also not ideal for assets remotely located or widely spaced, such as offshore wind turbines, as sensor installation will be difficult, time-consuming, and expensive. Additionally, these sensors need to be powered by a wired power source or by a battery requiring periodic replacement. Finally, these types of sensors can be damaged if used in harsh conditions, such as a conveyor moving hot plates of steel, or ATEX zones with explosive atmospheres.
In recent years, a new technology named motor current signature analysis (MCSA) has emerged that has many advantages over the techniques mentioned above. MCSA is an innovative, AI-based technology that monitors the electrical signals feeding AC motors and compares conditions against a library of data fingerprints. Its advantages include simpler installation in a wider range of applications, reduced equipment failures, longer lifespans, lower total-cost-of-ownership, and shorter payback period. In my next post, we will have a close look at this exciting innovation.
For More Information about Condition-based Monitoring
As part of our complete motor management solutions portfolio, EcoStruxure Asset Advisor for Electrical Distribution now includes condition-based monitoring of rotating equipment enabled by this exciting MCSA technology. Our fully integrated and certified solution includes motor sensors installed inside the MCC and connected to the cloud via dedicated data acquisition devices and gateways, with the complete architecture adhering to strict cybersecurity guidelines. The solution offers alarms, an integrated dashboard, and the support of our expert advisors. Also, learn more about asset performance management best practices, or try our asset performance management ROI calculator.
