A Step By Step Guide to Choosing the Right Maintenance Strategy for Your Equipment
When choosing a maintenance strategy for a given piece of equipment, it may be tempting to go with either the most effective or least expensive option.
While predictive maintenance is seen as one of the best ways to improve productivity, safety, and equipment downtime, it may not always be the best option for your situation. It comes with its associated costs, so it may not always be cost effective. Other maintenance strategies are often more appropriate.
Here, we’ll discuss how to choose the right maintenance strategy for your equipment.
Two Factors to Consider
When determining the right maintenance strategy for a given piece of equipment, you’ll have two primary factors to consider:
- The cost of equipment failure
- The ease of monitoring the equipment
Both of these will form the basis of your maintenance strategy for each piece of equipment.
Cost of equipment failure
The first factor is the cost of equipment failure. Essentially, if the asset breaks down, what impact will that have?
One of the costs associated with equipment failure is equipment downtime. The longer a piece of equipment is down, the more it’s going to cost. Given that the U.S. loses over $647 billion every year due to machine downtime, certain breakdowns are definitely worth preventing, especially for equipment that’s central to keeping your processes running.
Downtime isn’t the only factor to consider in overall costs, however. Repair costs, safety, and environmental impacts are also concerns well worth considering. If a given failure mode would result in injury to your employees or others, that would be worth preventing as well.
Ease of monitoring
The second factor is ease of monitoring. Watching over each piece of equipment incurs a cost. If the cost of monitoring a given asset would be more than that of the failure mode it prevents, it may not be worth implementing.
Where monitoring is more expensive, maintenance strategies that require less vigilance may be more appropriate. For instance, if it would cost too much to install sensors on a piece of equipment, you might be better served with a schedule-based preventive maintenance plan.
Step 1: Laying the Ground Work
Before you actually get started with choosing a maintenance strategy, you need to make sure you have the necessary foundation to handle that process. Specifically, you’ll need a team and sufficient maintenance data.
The team you put together for this planning process needs to consist of personnel from different departments. Making sure maintenance, operations, engineering, and so forth are involved grants you the advantage of having multiple skillsets and areas of expertise at the table, and it ultimately ensures everyone affected is represented.
This isn’t just a one-off committee either. This team will meet on a semi-regular basis to assess your current maintenance strategies and make adjustments as needed.
In addition to a team, you’ll need some maintenance data to work with as well. Particularly, metrics such as mean time between failures (MTBF) and overall equipment effectiveness (OEE) will be especially useful during the next step.
Step 2: Criticality Analysis
Criticality analysis is the way your team will determine how much an asset will cost you if it fails. The higher an asset’s criticality, the higher its potential costs. Some facilities evaluate criticality strictly by the impact an equipment failure would have on their process. Others use a more holistic approach, evaluating the effects failure would have on safety, maintenance costs, production, and the environment, as in the graphic below.
Under each category, rank the cost of a given failure on a scale from one to five, with one being the least severe and five representing disastrous consequences.
The higher the ranking, the more mature the maintenance strategy is for that asset.
For example, suppose the staff of a toy manufacturing plant is trying to determine the best maintenance strategy for their thousands of feet of conveyor belts. Looking at their data on past equipment failures, they find that it typically takes four hours to pin down the location and cause of the breakdown and to make the needed repairs. No major safety or environmental risks occur (aside from some spilled pieces posing a minor hazard), and the repairs typically aren’t very expensive. As such, their ratings would look like this:
Overall, they’d rate their conveyor system’s cost of failure as 2.
Let’s look at another example. An oil refinery is developing a maintenance strategy for their pipelines. Given that failure could result in significant losses, including disastrous consequences for their employees’ safety and the environment, they rate it a 5.
Step 3: Assess Costs of Different Strategies
Once you have a clear ranking of what each asset might cost upon failure, you’ll need to assess the possible strategies to use on each one. Typically, the more monitoring intensive a strategy is, the more it will cost. As such, the possible strategies you’d use might be ranked like so from high to low cost:
- Predictive maintenance (highest cost)
- Condition-based maintenance
- Scheduled preventive maintenance
- Run-to-failure maintenance (lowest cost)
In our conveyor belt example, the cost of monitoring thousands of feet of belt would likely be fairly expensive, especially if some parts aren’t readily accessible. Perhaps the most efficient methods would be ultrasound or infrared, neither of which would require physical contact, but which both would involve consistent effort. On a 1 to 5 scale, the team might rate this one a 3, right in the middle.
The oil refinery’s pipelines might offer a similar challenge, especially since many pipes might be buried or hidden behind other equipment. Again, ultrasound would likely be the tool to use, and the time it would take to monitor each pipeline means the team would rate the cost at around 2, given the total cost of the pipelines.
Step 4: Choose a Maintenance Strategy
With the cost of failure and the cost of maintenance in hand, it’s time to determine the best maintenance strategy for your equipment. Using our chart from earlier, each of our example companies plots their assets:
Since the cost of monitoring the toy company’s conveyor system puts it right on the line, they could potentially opt for either. They decide to try condition-based maintenance to see if it might reduce maintenance costs over time.
Meanwhile, the oil refinery plans to implement a predictive maintenance strategy using ultrasound and predictive analytics.
Step 5: Implement Your Strategy
Once you determine the strategy to use for each asset, it’s time to implement it. In some cases, doing so may represent a major shift in your maintenance team’s culture, so this will take some planning.
For instance, the toy manufacturer has been using a run-to-failure approach with their conveyor system. As such, switching over to a condition-based model will be a bit of a jump, though they do have some recurring PMs in place on other assets. They’ll need to train their maintenance technicians or equipment operators to periodically check their system with ultrasound and log the data. As that data builds up, they’ll need to be aware of when the readings look abnormal.
For the oil refinery, they’ve been using some condition-based monitoring on other equipment. Implementing their new strategy for monitoring their pipelines is simply a matter of adding predictive analytics to their current strategy, training their personnel to use it, and adapting their work order planning practices accordingly.
Step 6: Monitor Your Progress and Make Adjustments
Once you’ve implemented your maintenance strategy, it’s not the end. You need to monitor its progress and make adjustments as you go. Logging work orders and costs into your CMMS, seeing if downtime decreases, and so forth are all part of this process.
Going back to our examples:
As the toy manufacturer implements a condition-based maintenance strategy, they find that production does in fact increase, which lines up with current research on CBM. They decide to continue on with this strategy, but they do make a few tweaks to improve efficiency. That way, they’ll pay off the investment they made in their ultrasound equipment a little faster.
The oil refinery’s attempts to implement predictive analytics don’t quite pan out as hoped. They made the mistake of focusing on software selection without training their team in the skills they’d need to use it. The strategy itself wasn’t necessarily wrong, and the software they used was top-notch—they just didn’t implement the strategy well. As a result, they resolve to train their personnel in using data to plan maintenance work.
Following These Steps to Choose a Maintenance Strategy
As you look through these steps, consider how they’d look in your facility. Get a team together, make sure you draw on as much data as possible, and work together to select a maintenance strategy that makes sense for each piece of equipment in your facility.