There are many metrics that operations and maintenance can use to track progress, but a simple, solid definition of success focuses on return on investment.
For every strategy, from reactive to preventive and even predictive, the goal is to get the most uptime from the least maintenance. It’s a straightforward goal, but a comprehensive pursuit, and departments need to carefully control not only what they do but also when they do it.
Usage-based maintenance is how you can dial in timing for savings that can cascade across facilities at multiple sites. It’s how you get the biggest bang for your maintenance buck.
And because of the data sets involved, the bigger your enterprise, the more value usage-based maintenance can deliver.
What is usage-based maintenance?
Just like the name implies, it’s a strategy focused on timing maintenance according to usage. What sets it apart is how it allows you to borrow a lot of the good parts of other maintenance strategies. So, just like meter-based maintenance, it relies on tracking usage. And just like predictive maintenance, it helps you leverage past and current data points to help you plan and prepare for the future.
What are the differences between usage-based and meter-based maintenance?
Meter-based maintenance is directly tied to usage. So, if you say you need to change the oil in your forklift every 250 hours, as soon as you see the right numbers on the meter, you change the oil. Because you’re matching it to usage, you don’t have to worry about doing too much or too little maintenance.
But the problem is you also never know exactly when you’re going to hit that 250-hour mark, making it harder to line up the people and parts you need to get the job done.
With usage-based maintenance, though, you avoid this problem by adding a few more data points so you can make an accurate prediction about when to do the maintenance.
With meter-based maintenance, you know two things: when to do the maintenance and where the meter is now. With usage, you know those two plus the average usage based on historical data. In this example, it would be an average number of hours of use per day.
For example, you might have:
- 250 hours between changes
- 100 hours since last change
- 10 hours a day average usage
You need another 150 hours before the next oil change, which is 15 days away, based on your average use. With two weeks to plan, it’s easy to schedule the people and parts you need for that maintenance task.
What are the benefits of usage-based maintenance?
One of the important benefits is how it helps you avoid doing too little or too much maintenance. With too little, small issues have a chance to grow into big problems.
With too much, you’re wasting time and money doing work you didn’t have to. And there is a certain amount of risk, however small, associated with every preventive maintenance inspection and task (PM).
Every time a technician opens an asset, they might damage the access panel, add lubricant to the wrong reservoir, accidentally leave behind a tool that either gets damaged or becomes a monkey wrench, damaging the delicate internal parts and components.
Reactive vs proactive maintenance
Usage-based maintenance helps avoid costly downtime while also extending the useful life of assets and equipment. Because the team performs maintenance before failures, it’s easier and costs less. Instead of paying for rush deliveries on associated parts and then overtime to required labor, you can schedule work for when it’s the most economical: after the parts and materials are already in inventory and during regular work hours.
In fact, Eptura’s H1 Workplace Index reveals technicians require roughly twice as much time to complete reactive versus preventive work. The report incorporates independent research on enterprise companies across North America, Europe, and Asia Pacific, with insights from C-level, vice-president, and country-head leaders across departments, and leverages anonymous user data from more than 5,000 companies, including 19,000 buildings, 95.5 million desk bookings, and 25 million room bookings.
There are limitations built into the strategy, though.
What you’re doing is tracking usage with a meter under the assumption there is a connection between usage and condition. In the forklift example, the idea is that every 250 hours of use creates roughly the same amount of wear and tear.
But not all hours are equal. Some forklift drivers are more of the slow-and-steady types. And then there are the ones who put a lot more stress on the machine, with fast starts and short stops.
The principle holds true for many different classes of assets and equipment. The AC unit you’re running in the Arizona office is working harder per hour than the one in Seattle.
Why can usage-based maintenance deliver even more value to enterprise-level organizations?
Predicting the best time to perform maintenance depends on the accuracy of your averages. If you’re running two forklifts, it’s a small data set, which means the average runtime per day might not accurately reflect reality. But if you have multiple fleets spread over various locations, your data set is large enough to reduce the influence of outliers. Armed with a better average, the maintenance team can produce better PM schedules.
The same applies to any other repeating assets or equipment under usage-based maintenance. For example, vehicles, HVAC, pumps, and conveyor belts.
So, a logistics company with warehouses located across the country can leverage large data sets into accurate averages. And companies with a large real estate portfolio can look at HVAC usage across buildings and floors.
Implementing usage-based maintenance starts with a unified asset and facility management solution. Companies can automate data capture, manage work orders and PMs, track inventory, and generate reports for better budgeting.
With a unified system, they solve the problem of siloed information, supporting sharing and collaboration between teams, across the enterprise. Once they have accurate records on usage, facility and maintenance teams can create PMs specific to each asset before adding them to the schedule.