Scott Stukel, CMRP, Director of Asset Management and Reliability at Total Resource Management

In the world of asset management and reliability we are constantly bombarded with advances in technology that claim to give us future-now asset intelligence capabilities to analytically predict failures and autonomously operate and maintain our equipment better. But just because we CAN DO IT we have to ask ourselves SHOULD WE DO IT. Does it make sense to embark on these often complex and expensive high-tech journeys when we still struggle with asset and maintenance management basics?

Throughout my day to day travels and business interactions I am fortunate to have the opportunity to explore the cool world of technology for asset management and asset intelligence. I see software and tech that can do pretty much everything, from digital twins that allow you to replicate your equipment virtually to predictive solutions that can digest millions of data points and spit out meaningful analytical models. Don’t get me wrong, I’m a gadget junkie-nerd and pride myself with riding on the bow wave of cutting edge tech, but as one of my college professors repeatedly said, “an engineer isn’t an engineer if they don’t focus on cost and value” so that pushes me to dig into each of these solutions to weigh the benefits versus the effort and cost. So, what is the best way to begin to use this technology?

Most reliability and maintenance organizations still struggle with asset management basics. A large percentage of them still practice time-based preventive maintenance nearly 100% of the time. In instances where they are able to trigger maintenance from condition, it is only because someone has collected gauge readings or operating conditions of equipment and have typed it into a spreadsheet or in some cases into their enterprise asset management (EAM) system or computerized maintenance management system (CMMS). When advanced predictive and cognitive asset management solutions are introduced to the vast majority of these folks, they love the idea but can’t see the value in it. They can see the vision but recognize the extreme gap between where they are today and what it will take to reach the future state. In most cases they can’t justify taking the leap.

There is a middle ground, a place where you can achieve significant success and advance your asset management capabilities without too much disruption to business as usual. The starting point is not to try to dive into the deep end of advanced, expensive predictive and cognitive technology. Instead you should focus first on utilizing existing equipment SCADA information, sensors/devices, and other asset data to move the needle from traditional periodic to event-driven maintenance and asset performance monitoring. It has been proven time and again by numerous case studies that there is tremendous value in shifting from time-based to condition-based maintenance. This is the place to start.

Set a goal of evolving your reliability and maintenance program to utilize equipment condition to perform work when the asset needs it, not when the calendar dictates. I’m not saying that all time-based activities are bad, most likely you have many tasks that you are performing at some specified time interval that you most likely could do when certain conditions are met. In many cases you will find that data is already being collected in your SCADA historian or that you are receiving it from devices/sensors already installed on the equipment. Perform a simplified PM review or RCM analysis to determine what type of condition data can help you optimize your maintenance approach and then get it to your EAM/CMMS to trigger your maintenance work.

There is a technical component to this. The key to making this happen is to have a robust and flexible, yet simple, IoT Adapter/Bridge that seamlessly connects your devices, SCADA, or other control/monitoring systems to your EAM or CMMS. Otherwise you will need to either program a custom interface between the systems or have someone read the values from one place and type them into the other. Depending on your needs and architecture, an IoT adapter/bridge may be available from your EAM/CMMS provider, from your SCADA vendor, or from a third party. One of these is TRM’s IoT Edge which is available for use with Maximo or can be configured as standalone for other EAM/CMMS products.

Empowered with your ability to connect SCADA, sensor/device, and other data from your equipment, you will then be able to generate work based on condition instead of time. In addition, the same data can trigger alerts and alarms, notifying you that there is a failure or abnormal condition that requires immediate attention. Furthermore, you will have access to relevant asset condition and performance data inside your EAM/CMMS, enabling you to analyze and report there as well as correlate it with work order and other maintenance data.

It is easy to see the value in having the ability to leverage existing SCADA and sensor/device (IoT) data to enhance your asset management, maintenance, and reliability. Furthermore, it is possible to achieve these results without the high cost and complexity of advanced predictive and cognitive solutions. Down the road once you have optimized your condition based asset management capabilities, then explore how those evolved technologies can further benefit you.

If you have any feedback or would like to discuss how you can employ simplified IoT and condition based maintenance please don’t hesitate to message me.