Maintenance Predictive Maintenance Reliability

Move PdM To The Front Burner

EP Editorial Staff | March 1, 2022

Implementing an IIoT-based PdM program can help you make better use of your limited maintenance resources by cutting down on functions such as greasing bearings.

View IIOT-based PdM as a way to start maximizing resources now, not as a long-range project.

By Maureen Gribble, UE Systems

In the face of predictable and unpredictable challenges, the best response is to address those you can control and prepare (as best you can) for those you cannot. We can’t say when the supply chain will break down next, and we don’t know how long it will take to find the next candidate for that open position. Now, more than ever, it is important for operations to escape the cycle of reactive maintenance and move to a more predictive approach.

You’ve heard it before: The answer to today’s problems is the latest technology. While it’s common to hear that a predictive maintenance (PdM) approach, empowered by Industrial Internet of Things (IIoT) technology, is the answer to your reliability or maintenance woes, the practical reality of implementing PdM strategies and technology is often not so simple.

No amount of encouraging words about the theoretical efficiency of a PdM approach is going to loosen your schedule so you can make the metrics, reporting, alarm limits, and other program-level decisions that take time and focus to get right. Compared to just reacting as break downs occur, it’s easy to see why predicting and preventing failure would be more efficient. If understanding this concept is all it takes, why isn’t everyone already using the most cutting-edge methods available?

Remote Monitoring

Traditional maintenance schedules are time- rather than condition-based. Although this approach may be simpler from a planning and scheduling perspective, it is far from optimal in terms of machine health.

A machine or component’s decline toward a failure condition is rarely linear. Remote condition-monitoring tools provide accurate data on machine health and transform maintenance schedules, so teams are spending valuable time on work that is actually needed, not just because it’s on the schedule.

By installing monitoring sensors of various kinds (ultrasound, vibration, motion, fluid), assets can provide an operator or technician with a constant flow of data. Whether the data is complex or simple to understand, a good IIoT solution will notify technicians of problems in a clear and timely manner, give them insight, and suggest how to prevent failure from happening.

If an IIoT solution requires months of training or years of experience to properly implement, it may be difficult to find or retain workers who have acquired such valuable skills. Instead, talk to your supplier about ways to simplify alert and alarm interpretation, making it easier to train or cross-train employees to minimize the negative impact of workforce shortages.

When sensors detect increased bearing friction, these single-point lubricators inject grease until the friction returns to the baseline level. This automation is one example of eliminating manual functions that prevent maintenance professionals from working to advance PdM programs.

Cloud-based Data 

The data flowing from these sensors may output to your CMMS or another system. A cloud-based platform can extend these benefits, allowing remote access from anywhere within a secure environment. This opens the potential for centralized monitoring.

Captured data is continuously analyzed by the system itself or its human operator and trended against historical data. The richer the data, the better a remote-monitoring system can suggest a maintenance schedule that accommodates the decline of an asset, preventing the plant from overspending in maintenance labor and parts. Even with the many IIoT and remote-monitoring success stories that exist, selling leadership on a new PdM implementation or finding the time to get it done is not always simple.

Barriers to Implementing PdM

Looking at most of the available advice, we may begin to question whether a predictive strategy is worth developing or even possible if day-to-day tasks are already difficult to keep up with on their own. As with most big undertakings, the answer is to start with manageable steps that lead to small victories. A couple hours of lubrication work orders saved here, a breakdown avoided there, and soon you’ll start to see a light at the end of the tunnel. You don’t need a large reliability or maintenance team to unlock the smaller benefits or savings that come with a predictive or even proactive maintenance approach. 

Many experts agree that a new predictive-maintenance initiative should usually begin with a quantitative criticality assessment. Often, the implication is that the most critical equipment is the heart of the plant and where you should focus efforts to achieve the largest benefits.

Although this is not always the case, critical equipment is often larger and more complex. Focusing efforts on such assets may mean that the minimum investment required to achieve success is relatively high if you want to build a system that will prevent the most critical failures and potentially save millions in unplanned downtime and production losses. Doing so can be difficult to implement in the real world.

Also, changes related to the most critical systems are not often the simplest to plan, especially if you’re already stuck in a firefighting, reactive maintenance cycle. In such cases, mid-criticality or even low-criticality equipment might be a better place to start because it’s a smaller, more manageable commitment with a higher likelihood of success.

Impact vs. Criticality

Instead of relying on criticality to decide which assets to focus on first, consider other ways that PdM or IIoT solutions could have a positive impact on your program. Are technicians spending a lot of valuable time with simple, repetitive tasks such as regreasing bearings? Are certain tasks especially time-consuming, difficult, or dangerous because of the asset environment or other factors? Are you having trouble keeping certain roles filled? The most powerful IIoT tools don’t replace the human element, they empower technicians to make better decisions and get more done while spending less time and resources. 

These small, periodic tasks prolong asset life and are much cheaper to carry out than making major, last-minute repairs after failure has occurred. With remote-monitoring capabilities, there are simply fewer inspection and walk-down tasks to eat up the day. Some systems can even perform the maintenance task for you.

Empowering, Not Replacing

Remote monitoring and IIoT can take a significant amount work off a maintenance technician’s plate. Rather than treating an automated regreasing system as a replacement for a lubrication technician, it’s better understood as a way to extend the power and capabilities of that technician. Without the need to spend a day walking down and greasing electric motor bearings, that technician can use the extra time to work on reliability and drive long-term success.

Although technology and tools will continue to develop, our own mindset related to these resources must develop as well. If we’re stuck seeing PdM as a “major future project,” we’re doomed to be stuck in the past. Instead, we should see this technology for what it is—a way to take charge of the little things we can control, allowing us to be better prepared for all those things we cannot. EP

Maureen Gribble is a Director, Certified Maintenance & Reliability Professional (CMRP), and certified Level I in Ultrasound at UE Systems Inc., Elmsford, NY (uesystems.com). 

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