MRO Magazine

How maintenance 4.0 technology will help bridge the skills gap

Can digital solutions and vibration sensors fill the maintenance skills gap?

November 10, 2022 | By John Bernet

Photo: Krittanut Unsombut/Getty images

Photo: Krittanut Unsombut/Getty images

Chances are, you’re already aware of the maintenance worker skills gap. This isn’t a new problem – it’s been around for at least 10 years. But every year, the problem seems to get worse.

Fewer young people are getting the training they need to diagnose and repair machine faults.

Maintenance managers and reliability engineers are seeing the pool of skilled workers get smaller and smaller. Meanwhile, qualified workers are hitting retirement age and leaving the workforce.

More and more plants are turning to technology to bolster their maintenance programs. This begs the question – can digital solutions and vibration sensors fill the maintenance skills gap?


The answer isn’t simple. It’s important to maintain some perspective and stay realistic about what technology can do. Today’s best tools can’t replace a human workforce. Even with the best technology, you’ll still need human know-how and experience to keep your operation up and running smoothly.

But at the same time, the right connected tools and sensors, coupled with a solid computerized maintenance management system (CMMS), can help you to shift to a predictive maintenance strategy, so that you can identify and diagnose machine faults early. In the not-too-distant future, AI-enabled analysis software will push these capabilities even further. This means that you will be able to keep your machines up and running for longer, even if you’re operating with a lean maintenance team. If you manage this process correctly, the results can be revolutionary.

What is predictive maintenance?
Predictive maintenance is a proactive strategy for keeping your assets up and running. It’s premised on the idea that you should only perform the maintenance work on an as-needed basis. Instead of routinely servicing your assets, your maintenance team will monitor them for signs that they need repair.

Predictive maintenance uses a network of vibration sensors that monitor the vibrations emitted by your equipment. They collect and store this data so that it can be analyzed for signs of fault.

Data collection isn’t new, of course. Maintenance teams have always collected data, simply by observing the machines in their plants and keeping track of how they operated.

As plants get bigger and take on more equipment it’s almost impossible for a maintenance team to directly monitor every single asset. That’s why sensors are so important, especially as the pool of skilled workers is shrinking.
Here’s how a plant can use vibration monitoring sensors, CMMS, and analysis software to make the most of a lean maintenance team.

Step one: performing triage
On its own, data doesn’t add value to your maintenance team. Raw data needs to be organized and analyzed so that your maintenance teams can start to spot patterns. CMMS software can integrate with sensors and software tools so you can organize and analyze your vibration data and put it to use.

The first step is simply identifying any change in vibration emissions. Once a machine shifts from its baseline vibration signature, that’s a sign that it needs to be examined more closely.

This stage of proactive maintenance – looking for changes from the baseline – fills the same function as the triage process in a doctor’s office.

In a doctor’s office, nurses perform the first level of triage. They collect data on patients’ weight, blood pressure, and temperature. That’s usually enough to tell them whether a patient is healthy or not and in need of care.

In the same way, your CMMS software uses the vibration data to perform triage on your assets. It scans for signs of anything unusual which could indicate a new or developing fault.

Triage saves your team time, energy, and funds by allowing you to focus your energy on the machines that actually need to be repaired. You won’t need to waste labour or time on the equipment that’s already
running smoothly.

Step two: CMMS, analysis software, and work orders
Vibration analysis software can perform diagnostic tests to identify many common machine faults.
To date, vibration analysis software can diagnose the four most common faults in rotating machinery, namely, imbalance, shaft misalignment, looseness, and bearing faults.

To continue the hospital analogy, the vibration analysis software is like the primary care physicians who can diagnose patients with common ailments.

And, just as the primary care doctors need to be “called in” by the nurse on duty, the algorithms also need to be called in to start their diagnostic process.

That’s where your CMMS comes in. You can set up your CMMS to automatically generate a work order once vibration levels deviate from the norm. That work order will trigger software to assess and diagnose the machine in question.

Step three: scheduling repairs
Once the software has diagnosed the machine fault, your CMMS can automatically generate a work order to review recommended repairs based on that diagnosis.

The CMMS lets teams review the recommendation, then schedule the work based on when your maintenance teams are available, or when it’s convenient to shut down your equipment for repairs.
Most of the time, vibration monitoring and analysis software will alert you to machine faults long before the problems become serious. This means that you will have plenty of time to schedule maintenance at a convenient point for you.

The reconfigured workforce
Shifting to a proactive maintenance strategy doesn’t mean that you won’t need maintenance workers
any longer.

Instead, it means that you’ll be able to re-configure your workforce so that you get the best possible work out of everyone on your small maintenance team. Building a tech-centered approach means considering what you’ll still need from your
maintenance team.

In most cases, you will need a group of maintenance experts who have the ability to implement a proactive maintenance strategy. That means knowing which machines vibration analysis software is capable of diagnosing, and which machines are too complex. In the future, it will require a similar understand of the limits of AI-enabled vibration analysis software.

If we go back to the hospital analogy, it’s helpful to think of maintenance experts as the specialists in various medical fields. They can diagnose problems that a primary care physician might not know enough about. They can also recommend treatment for these problems.

So, if your machinery has complex faults that AI cannot diagnose, your maintenance experts are on-hand to identify the issues and figure out how to address them.

Bear in mind that you can also outsource the expert level, as needed. If you’re operating with a small maintenance crew, then it’s worth spending some time looking for a trusted partner to advise you on your maintenance needs.

Implementing a tech transformation
A successful tech transformation should happen gradually. Too many businesses try to overhaul their whole operation at once. This can lead to chaos and, eventually, disillusionment in the process.

Instead, it’s a good idea to start with a pilot program. Choose 10 or 15 simple rotating machines that are prone to breakdowns. Test your proactive maintenance program on those machines alone. Chances are, these are the machines that have already cost your operation a good deal of time and money. You have the potential to show a major change by introducing technology here.

Getting decision makers on-board
Building a tech-centered maintenance approach takes an investment of time and money. This can raise challenges when it comes to getting your key decision makers on board.

That’s another reason that it makes sense to introduce the new approach gradually as wins happen and
prove results.

Start with a pilot program and then gradually add more machines to your program; it’s a good idea to stick with introducing 10 or 15 new machines at a time in phases. As your programs succeed, it will be easier to get your decision makers excited about expanding it.

CMMS can also help you here. By keeping track of your work orders, CMMS documents reductions in breakdowns and in maintenance work orders.

If your company has a change in leadership, you’ll be able to use those work orders to show your new boss how successful the new maintenance approach has been. They’ll be able to see that you are keeping your equipment up and running and that you’ve cut back on routine maintenance costs.

Because ultimately, that’s the goal – decreasing downtime, increasing productivity, and making sure that you’re not overspending on unnecessary maintenance. And that’s what a carefully designed predictive maintenance program can deliver.

Building this framework of connected sensors and software now will prepare your organization for the day that AI-enabled maintenance software is ready to take operations to yet another level.
Article provided by Fluke.


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