IIoT / Industrial Motors / Vibration Analysis / Infrared Thermography / Predictive Maintenance / Condition Monitoring / Preventive Maintenance / Temperature Monitoring

Monetize your knowledge: PM and PdM for electric motors

Vibration and temperature are key factors to watch in IoT-enabled condition monitoring.

By Thomas Schardt and Pranesh Rao, Nidec Motor Corp., and Chris Diak, Motion Industries

Maintaining operation of a production line can be a lot like maintaining the health of a person who is predisposed to heart disease. For the best possible outcome, you must know the warning signs of trouble; you need to monitor that person continuously; and you must be prepared to act quickly should conditions change.

To understand why, consider what happened recently at the manufacturing plant of one of our company’s key suppliers.

This plant operates several production lines, two of which have been equipped with a monitoring system that remotely monitors the lines’ condition. While a heart monitor might use sensors that check for irregular heartbeats, this system uses sensors to closely watch motor vibration.

Shortly after the installation of this monitoring system, one production line’s vibration levels began exceeding the operating parameters that had been established for the motor. Analysis of the vibration data indicated that a motor bearing on that line was on the verge of failure. Further review suggested that the bearing could function for a few more days – enough time to secure a replacement part that could be installed during a controlled shutdown.

Three days later, that’s precisely what the plant did. Production was moved to another line while the bearing was replaced at a fraction of the cost that would have been incurred had the equipment failed unexpectedly. Think of a heart patient whose heart monitor readings suggest an adjustment to his or her blood pressure medication.

Consider now what might have happened had the production line not been continuously monitored. In that case, the motor would have failed and production would have come to an immediate halt while a maintenance team worked to identify the problem.

In addition to diagnostic and repair costs, the company would have faced rush charges, lost production, and possible overtime wages – not to mention the potential customer dissatisfaction brought on by delayed product shipment. The cost of an undetected bearing failure could have easily been 20 times the amount of preventive action. To complete our medical analogy, it would be the difference between a change in medication and emergency open heart surgery.

Positive outcomes, by contrast, result from parties that have the foresight to monitor very simple things: heartbeats and motor vibration levels.

Excess vibration is a warning sign for many potential equipment problems. The vibration signature of a specific piece of machinery, in fact, provides more information about the machine’s mechanical condition than any other factor. But it is not the only thing to monitor. Comparing equipment temperature, noise profiles, and a host of other technology-specific factors can also provide additional insights into equipment condition.

All of this equipment monitoring is at the core of a condition-based (predictive) maintenance program.

Striking a balance between PM and PdM

Many plants today still rely on service contractors that provide regularly scheduled preventive maintenance on critical equipment. This approach – a giant step past the traditional, reactive “we’ll fix it when it breaks” approach – involves following manufacturers’ maintenance guidelines to reduce unscheduled equipment failure and unplanned downtime. Preventive maintenance has a long history of improving safety and bottom-line results.

To go to the next level – condition-based, or predictive maintenance (PdM) – industrial companies and their maintenance, repair, and overhaul (MRO) service contractors will need software-based tools that enable them to access the vast amounts of operational and equipment health data manufacturers already own but are not fully utilizing. The efficiencies possible with a true predictive maintenance approach will depend on the software available to sift through millions of data points to identify those that align with actual equipment condition and performance.

PdM has been improved by technological advances in sensors and in connectivity and communications tools for streaming live data, and declining prices for these have made them more accessible. Special analytical software developed for the industrial internet of things (IIoT) has added needed capabilities, too. Without data analytics, defining an optimal maintenance strategy for critical equipment is like a tightrope walk between operations and maintenance costs on the one hand and the potential cost of an unexpected or unscheduled equipment failure on the other.

Servicing machinery is most cost-effective if it’s done when it is needed (within certain limits). If equipment repairs are addressed too early, a company will spend more on replacement parts and upkeep than it would if maintenance schedules were determined based solely on equipment condition. If it waits too long, on the other hand, deterioration can progress too far, resulting in higher costs to bring equipment performance back to acceptable levels.

The challenge that manufacturers, OEMs, and service providers alike face is striking the right balance between preventive and predictive maintenance by finding tools to help bridge the gap. These tools reduce the cost of preventive maintenance while also helping to define the scope of predictive maintenance and determine the best times for performing it, resulting in a higher overall equipment effectiveness.

Especially valuable are solutions that make it possible to monitor and evaluate the health condition of critical equipment remotely and in near real-time condition.

Monetize your knowledge

The foundation of improved machine and equipment reliability is continuous condition monitoring. Rather than replacing highly trained vibration and other maintenance experts, remote monitoring tools provide these professionals with remote access to data in real-time. This information helps them recognize the signs of impending failures early and avert bigger problems.

These tools also can help isolate the cause of errors using data analysis and comparisons of equipment’s specific vibration, temperature, noise, or other characteristics as a guide.

Remote condition monitoring tools also allow equipment manufacturers and service companies to develop new service models that appeal to a broader customer base, enabling them to offer cost-effective predictive maintenance approaches that do not require customers to buy or maintain their own software. This approach may be especially appealing to small- and medium-size enterprises that desire but could not previously afford real-time streaming analytics.

As the knowledge base grows and more manufacturers and service providers draw on analytics to support maintenance decisions, the value of predictive maintenance will increase. Not only can it help maximize equipment service life without increasing the risk of failure, but also condition monitoring can contribute to continuous improvement programs that improve machine reliability and reduce operating costs.

Again, predictive maintenance is a lot like predictive healthcare. It’s all about monitoring critical functions, collecting data from different sources, analyzing it, and predicting potential failures as accurately as possible. Most importantly, it’s about acting on that information.

With a remote equipment monitoring platform, data can be accessed anytime from anywhere using a browser on a web-enabled device. Events won’t get missed, and no time is required to drive to a location for an on-site inspection. Continuous real-time data is available at a fraction of the cost and time the industry was and is used to.

It is one more piece of proof that we have officially entered the age of predictive analytics. Real-time data collected through wireless monitoring can now identify patterns that make it possible not only to intervene to prevent imminent breakdowns but also to predict future events.

Many new products are hitting the market intending to provide the next best thing. Only every blue moon do you witness the birth of a technology that could help change the entire landscape of how we approach maintenance and operations on the factory floor. We in industry challenge ourselves to stay atop the latest technologies and automation trends, with the goal of greater and faster production.

As the IIoT begins to develop, flourish, and become standard, some facilities may be unsure of the best course forward. Being proactive and engaging a qualified automation specialist can assist with the transition. Allowing the technology to do its job can play a big role in reliability and cost-saving initiatives, and we’ll have every reason to continue to embrace it.