Asset maintenance is the inescapable part of any factory floor. In 2020, nearly 47% of factories in the US spent between 21% to 40% of their operating budget on maintaining their equipment.
That is quite the money sink.
This is specially made more egregious by the fact that US companies use almost $40 billion in outdated equipment, which is believed to be the leading cause of unplanned downtime.
With that said, it is then no wonder that maintenance is such a hot topic, especially when it comes to the costs, efficiency, and downtimes related to it.
In this article, we’re going to address those questions precisely. In the text below, you’ll find the analysis of the benefits of the three most frequently-used maintenance types, as well as their drawbacks.
Reactive Maintenance – What is It?
Reactive maintenance, also known as corrective maintenance, is the most basic type of upkeep of equipment. It centers around performing corrective work on assets that have already broken down, fixing them, and bringing them up to speed.
The biggest advantage of this kind of maintenance lies in its relatively low operational cost. Considering the machine is fixed only once it breaks down, you only need to pay once, and you only need to suffer downtime once.
However, this is also corrective maintenance’s greatest weakness. See, the idea of fixing machines only once they break hinges on keeping the asset running for as long as possible and generating as much production from it as possible.
Once the machine breaks, however, now you’re faced with unplanned downtime and costs that could easily exceed the revenue generated by the machine, which, in turn, has a majorly negative impact on that asset’s overall ROI.
Be that as it may, reactive maintenance is still essential. The truth of the matter is, that machines break down, sometimes unexpectedly, either due to insufficient maintenance, unskilled labor, or poor design in the first place. When that happens, you will have to shut down production for a while as you address the issue.
Preventive Maintenance – A Step Up?
Naturally, most companies will work hard on properly performing upkeep on their assets to keep them running for longer and to prevent unnecessary downtimes and the costs tied to it. This is why most businesses turn to preventive maintenance.
Preventive maintenance is a set of practices centered around performing regular, periodical maintenance of machines and assets within the factory.
As such, preventive maintenance already trumps reactive maintenance by eliminating unexpected downtimes. Needless to say, you still have to halt production to perform the said maintenance, but predicted downtime is much easier to work with and around than your assets suddenly breaking.
Basically, the goal of preventive maintenance is the preservation of assets in the long run. This is also why such upkeep has a very high ROI, reaching up to 545%, whereas corrective upkeep might even plunge you in the red.
That said, in order to reach that ROI, you also have to sink quite a bit of money and man-hours into it to be effective.
You see, the core of preventive maintenance is regular maintenance. This means that your machines will have to be inspected at certain predetermined intervals, and parts will be swapped out regardless of whether they’ve run their course or are still usable.
This also means that you have to have skilled staff on hand to perform all the necessary diagnostics and part replacement. All this drives up the cost while also increasing downtime due to the necessary taking assets off the production line to have them checked out.
In the end, though, regularly diagnosing and replacing parts still has much higher benefits than running your assets into the ground, then replacing them. As we said, preventive maintenance extends the life of your assets and keeps them running for longer, thus generating higher ROI despite increased planned downtimes.
Predictive Maintenance – The Ultimate Solution?
Predictive maintenance, as its name suggests, centers around predicting failure points and reacting to them before they occur.
As such, predictive maintenance encompasses the advantages of both of the previous types of upkeep in order to create the ultimate maintenance model for your business.
Ultimately, PdM seeks to:
Reduce maintenance costs
Reduce planned and unplanned downtimes
Increase the efficiency of maintenance
Increase asset life span
Increase the overall efficiency of the production line
By not having to devote man-hours and funds to a regular diagnostic cycle, you’re freeing up your staff to do other important things while also having more money at the end of the day to invest in other assets.
Also, because you’re still, technically, performing prescriptive maintenance by predicting failures and addressing them before they happen, you’re still not experiencing the dreaded unplanned downtime or having to replace your assets completely.
So, how does PdM do it?
The core of this methodology is the Industrial Internet of Things (IIoT). IIoT is the concept, developed from IoT (Internet of Things), of having “smart” machines and assets that “talk” to each other and their users and are all integrated into one overarching network.
Twenty, or even ten years ago, this was but a concept. However, with the recent advances in AI technology and machine learning, this concept has slowly become a reality. Now, machines can be connected and can be made to communicate, and they do it via sensors.
These sensors are at the heart of IIoT. They enable the gathering of various types of data that are then transferred over the network into a computer mainframe that analyzes this data, thus, effectively performing diagnostics in real-time.
This data can then be used to, well, make predictions about the possible failures of your machinery. If a parameter is out of predefined bounds, this points to a possible problem, and you can react to it before any major damage occurs.
However, this also has another advantage that the two previous models don’t have – the ability to detect the source of the problem.
You see, with reactive maintenance, you’re just fixing a machine that’s already broken, and with PtM you’re performing regular maintenance of parts. However, both of these models only aim to alleviate the problem, not eliminate it altogether.
Due to the abundance of sensors all communicating with each other and the amount of data they produce, you are able to pinpoint the exact problem in your production line that’s reflecting on certain asset(s) down the line. And, once you address that problem, you’re eliminating all others connected to it.
From all this, it would seem that PdM is the way of the future and is the only maintenance model worth considering. But, in truth, predictive maintenance still has enough kinks in its process that put companies off.
For starters, this is by far the costliest and most complex model to implement. In order to fully appreciate predictive maintenance, you would either have to build your factories from the ground up with PdM in mind or figure out a way to introduce it into your already established infrastructure.
On top of that, you also need specialized, highly-trained help. This help is still hard to find and relatively expensive to hire, which drives the overall costs of implementation further up.
Finally, you have to have specialized software to analyze the specific data tied to your industry or to even your production process. Metal industry software is going to differ from software required for running an automobile plant and so on. You’ll often have to have custom software made by outside experts, which all cost money and time.
In the end, while predictive maintenance seems like a clear winner due to all the benefits it brings, the implementation methods of the concept are still young. However, PdM is truly the way of the future, and, in the coming years, we are very likely to see this concept crop up within an increasing number of companies across the world.
That said, this does not make the other two methods completely obsolete. Reactive maintenance is still the cornerstone of maintenance in general, and the high ROI of PtM, as well as its commonality, still proves to be undeniably attractive to businesses that don’t have the means to create the infrastructure for predictive maintenance.
Rick Seidl is a digital marketing specialist with a bachelor’s degree in Digital Media and Communications, based in Portland, Oregon. He carries a burning passion for digital marketing, social media, small business development, and establishing its presence in a digital world, and is currently quenching his thirst through writing about digital marketing and business strategies for House and Courtyard.