Nowadays, everyone and their dog has heard about predictive maintenance. But not a lot of people have full-fledged predictive strategies in place. If you’re in this group, you may still wonder whether or not predictive maintenance is really cost-effective. Will you get your investment back?
The benefits of predictive maintenance
You probably heard all about the benefits of predictive maintenance before. But we promise we have a point here! It’s too easy to fall down the “cost of predictive maintenance” vs “cost of reactive maintenance” rabbit hole. Nevertheless, we cannot measure cost-effectiveness just by taking into consideration the cost of maintenance itself.
Predictive maintenance eliminates downtime.
Reactive maintenance comes with high costs and it doesn’t avoid downtime. If predictive maintenance can eliminate hours of downtime, it might pay for itself with higher outputs and reliability. As an example, here’s the average unplanned downtime in the Oil and Gas Industry:
Source: Oden Technologies.
Predictive maintenance extends asset lifespans.
When you’re able to detect failures accurately and avoid breakdowns, even older assets become more reliable. That means you can get more return on investment per each piece of equipment. Modern asset management software can help track and optimize this reliability across your entire equipment portfolio.
Predictive maintenance avoids waste.
Research found that 30% of time-based preventive maintenance is unnecessary, which creates waste. (We’re sorry to give you the news.) If predictive maintenance avoids this, how much time and resources can you save?
Predictive maintenance is not intrusive.
Would you sign up for a medical check-up if that put your life at risk? Sometimes, preventive maintenance requires disassembling and reassembling activities, which increases the likelihood of a breakdown in the future and the costs that come with it.
Of course, implementing predictive maintenance strategies requires careful coordination of spare parts and resources. You can’t just predict when something will break – you need to have the right components ready to go. Inventory management software can ensure you have the right components available when predictive analytics indicate maintenance is needed, avoiding the nightmare scenario of knowing a failure is coming but being unable to prevent it.
Is predictive maintenance cost-effective?
As tempting as it all sounds, the question still lingers in the air. Is predictive maintenance really cost-effective? As any maintenance manager knows, most condition monitoring techniques – a non-negotiable condition for predictive maintenance – still come with high upfront costs. And then there’s still the cost of data modelling and analysis. While cmms software can help streamline these processes, for a lot of companies, it may be prohibitive. So one wonders if predictive maintenance is the oasis in the desert we all want it to be.
We set out to find the answer. According to a widely quoted McKinsey study published in 2018, predictive maintenance can improve maintenance efficiency and generate “substantial savings” in more ways than one:
- It reduces maintenance costs by 18-25%.
- Increases availability by 5-15%, which yields even more gains.
That same year, PWC released a report called “Predictive Maintenance 4.0 – Beyond the Hype: PdM delivers results”. The study surveyed 268 European companies from Belgium, Germany, and the Netherlands. It focused on how we move on from visual inspections to instrument inspections, real-time condition monitoring to the promising new world of real-time big data analytics (PdM 4.0).
Once again, the study suggested predictive maintenance is cost-effective for manufacturers:
- Companies decreased maintenance costs by 12% (less than in the McKinsey study, which pointed to 18-25%) and availability improved by 9%.
- Predictive maintenance also extends the lifetime of an aging asset by 20%.
- Reduced safety, health, environment and quality risks by 14%.
Both studies prove that predictive maintenance allows:
But here’s the thing – knowing when maintenance is needed is only half the battle. When predictive maintenance identifies potential issues, field service management software can efficiently dispatch technicians and coordinate repair activities before failures occur. It’s the difference between having a crystal ball and actually being able to act on what you see.
- more targeted maintenance (less wasteful repairs and inspections);
- predictable quality and improved reliability;
- better overall effectiveness (OEE);
- longer asset lifespans.
The plot thickens: how much does equipment downtime cost?
Another 2018 report by the CXP Group showed that 91% of businesses see a reduction in repair time and unplanned downtime, and 93% see improvement of aging infrastructure. Whether or not that means a positive return on investment depends on (1) how much those repairs would cost and (2) how much companies lose with unplanned downtime, but they’re undoubtedly promising statistics.
While we were trying to answer that question, we found a 2016 report by the Aberdeen Group. The report suggests that, at the time, unplanned equipment downtime cost, on average, $260.000 an hour (a 60% jump from 2014.) And how long does the average outage last? According to Machine Metrics, around 4 hours. Now, that’s a massive amount: $1.040.000 per outage on average! If only maintenance could prevent it…
But those are just average values and statistics, right? Surely your company is not losing around a million dollars (around £725.500) every time a machine goes out of service. So, how much does downtime cost your company? Start by calculating containment and repair costs. Then calculate the output you lost and what it represents in terms of revenue. Add any other costs you might incur (compensation to third parties, etc), and sum it up.
Now, if you’re managing a facility with multiple assets and systems (and let’s face it, most of us are), things get complicated fast. For facilities managing multiple assets and systems, facility management software can integrate predictive maintenance data across all equipment to provide a comprehensive view of facility health. Because trying to juggle predictive data from dozens of different machines manually? That’s a recipe for disaster.
These are not easy (or pleasant, for that matter) calculations. However, it’s absolutely necessary to assess how much you risk to lose every year. It gives you a threshold for how much you can invest and how soon you can expect return on investment. However, if you want to be thorough, we did some extra digging for you.
What’s the value of predictive maintenance?
Knowing how much downtime and repairs cost is a good start. If the cost of reactive maintenance is the same, then you won’t be saving anything. Now, when you’re comparing preventive and predictive maintenance, the choice isn’t as straight-forward.
And let’s not forget about the regulatory side of things – because compliance never sleeps. Predictive maintenance programs must also consider regulatory requirements, making compliance management software essential for documenting maintenance activities and ensuring adherence to industry standards. After all, what good is avoiding downtime if you end up facing regulatory penalties?
Predictive maintenance is more targeted, but it isn’t foolproof. How accurate is it? What’s the likelihood of predicting failures? And can you predict them with enough time? Packt has a tutorial so that you can do some modelling:
Net Savings = (Cost of Failure * [Expected Number of Failures – Expected True Predictions]) – (Proactive Repair Cost * [Expected True Positives + Expected False Positives])
For large organizations juggling multiple facilities and complex operations, the math gets even more intricate. Large organizations often rely on a cafm system to integrate predictive maintenance data with broader facility operations and space management functions. It’s about seeing the bigger picture – how maintenance decisions impact everything from space utilization to operational efficiency.
Is predictive maintenance cost-effective? Everything points to a solid “yes”, at least in manufacturing. Is it worth the investment for your company? When can you expect a return on investment? Monitor your key performance indicators, investigate condition-monitoring techniques, and do some math of your own.
