Half of all industrial companies now undertaking digital transformation or IoT-related projects say they do so in hopes of turning products into services and increasing sales. If you are among them, you might think again.
It’s not that the IoT cannot be monetized to deliver valuable benefits. It’s just that increased sales are not typically one of them. In fact, more than 60 percent of IoT initiatives stall at the Proof of Concept stage primarily because companies pursue them for the wrong reasons, lack stakeholder alignment or underestimate their complexity.
The fact is, adding sensors and communication capabilities to collect performance and condition data doesn’t create value. To maximize asset value, you must analyze that data and use the knowledge gained to act. Deployed properly, Industrial IoT makes it possible to improve product quality, increase operational efficiency, innovate new business models and more. Perhaps its greatest value is its ability to reduce costs through remote condition monitoring and diagnosis, both precursors to predictive maintenance.
Predictive maintenance is a game-changer
Take a preventive approach to maintenance risk; completing repairs before they’re needed and spending more on replacement parts and labor than necessary. Wait too long by taking a reactive approach, and it may cost even more in repairs, rush charges and production downtime. Unless the maintenance meets the highest standards, you also risk introducing problems that didn’t exist before.
The challenge manufacturers, OEMs and service providers face is striking the right balance, so required repairs are completed, precisely when needed. Condition-based maintenance makes that possible. Using an Asset Condition Monitoring Platform solution (ACMP), continuous condition monitoring makes it possible to monitor and evaluate the health condition of critical equipment remotely and in real time.
An ACMP lets you see how a product performs in the field. It helps you learn to recognize the signs and conditions that lead to failure, making it possible to not only time maintenance appropriately and pinpoint the scope of repairs, but also identify a problem’s root cause and prepare for the repair. The end goal: maximizing equipment’s useful life, while minimizing costly downtime, especially unexpected disruption.
To understand how it can be monetized, consider two examples.
Example #1: Monetizing an outdoor aggregate belt conveyor
A piece of equipment’s vibration signature usually provides more information about its mechanical condition than any other factor. However, it’s not the only thing to monitor. Comparing equipment temperature, noise and current profiles over time can also provide insights, as can other technology-specific factors.
That proved to be the case at a Colorado mining operation, where an aggregate belt conveyor was experiencing exceptional vibration. Inter-tied aggregate operations that move rocks via belt conveyors to rock crushers and separators always shake violently. A problem’s root cause is virtually impossible to identify by analyzing the vibration spectra alone. Rather, it requires analysis of vibration level trends in combination with other inputs.
In this case, Nidec’s continuous monitoring solution, which included sensors measuring vibration, equipment, and ambient temperatures, led a technician to a hot gearbox. By the time the gearbox failed, a replacement had been purchased. It was then replaced in under four hours, compared to the industry average of 60 hours of lost productivity, had the failure caught operators by surprise. That translates to an estimated six figures in cost avoidance.
Example #2: Monitoring critical assets in a manufacturing plant
Several production lines operated by one of our manufacturing clients have been equipped with a monitoring system and sensors for remote monitoring of vibration and temperature of a critical motor-pump combination.
After eight weeks of uneventful operation, vibration levels began exceeding established operating parameters. Analysis of the vibration spectra indicated the circulation pump bearing was deteriorating quickly and on the verge of failure. Further review suggested the bearing could function for a few more days—enough time to secure a replacement.
Three days later, that’s precisely what happened. Production temporarily moved to another line while the bearing was replaced during a controlled shutdown. Factor in rush charges, lost production and wages—not to mention delayed product shipment—and an undetected bearing failure could have easily cost ten times the amount spent.
Through careful monitoring, early detection and correct root cause identification; a controlled shutdown avoided any consequential damages and didn’t impact production output.
The challenges ahead
It takes new and different skills to install, operate and benefit from the use of condition monitoring systems. OEMs and end-users alike are concerned about how these changes might impact their workforces. They’re even more concerned about security and data protection risks posed by interconnected systems. Funding is also a question, as is how to intertie solutions into today’s production processes and future-proof them for tomorrow’s.
That’s why it’s best to start small by identifying your biggest pain points. Is there a particular asset, for example, that breaks down frequently? Size does not matter; it’s the downtime cost that counts. Define how a condition monitoring solution can address these points and take the first step forward.
When considering options, remember there is no perfect ACMP, and that any solution is only worthwhile if people actually use it. Choose plug-and-play solutions that are flexible, scalable and easy to deploy and use on new and existing equipment. Begin perhaps with a couple of sensors that measure vibration and temperature—and expand from there, adding current, flow, pressure and other variables, as needed.
The important thing is, get started. Collect data, analyze it, act and learn from it. And then repeat.
Properly applied, your new knowledge can be monetized by reducing operational costs while maximizing critical equipment’s service life without increasing the risk of failure. Real-time data and enhanced analytical capabilities allow better process control and asset utilization, reducing waste and raising productivity.