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Keep Score on Your Assets With a Criticality Analysis

6 min read

Okay, we all have our favorites — the assets we pat on the back with affection every day. They're often the brightest, shiniest or newest pieces of equipment, the ones you want to show off to friends and life partners. Maybe they light up when you touch them, giving that love back. But, the thing is, these assets might not be as important as you think they are. Or, at least, despite your best efforts, they're less reliable than they could be.

An asset criticality assessment reveals any faults or downtime risks. It's an impartial measurement that stacks your equipment side by side and asks, "What will really put me on the back foot first if something goes wrong?" Subsequently, you have guidance for what asset management to prioritize and which other parts of your workflow are necessary but not quite as urgent.

Asset criticality, then, doesn't let you play favorites unless there's a reason, saving you from more costs, frustrations and offline consequences for the equipment that has the biggest impact on your business. It's one of the most useful metrics we have for planning preventive maintenance.

Follow us to learn about failure and reliability in the asset lists that may be riskier and more vital than you realize …

Scoring failure and reliability risk

When we consider the challenges to ongoing maintenance, it pays to think holistically. An asset criticality assessment hangs beneath an umbrella of interrogations you should carry out to determine whether equipment is performing well and how it affects your processes. We call this FMECA: a failure mode, effects and criticality analysis. Kind of like gathering all of your friends in a room and asking when they let you down, but less brutal.

Generally, FMECA seeks to understand why machines and components fail, what potential consequences their failure has and how you can step in earlier or with more appropriate technical skills to solve the problem before it snowballs. You don't have to conduct an FMECA regularly (once a year is fine), although it's advisable if you're welcoming a fresh asset, using an asset in a new way or introducing additional processes to your organization. Some business methodologies, such as lean manufacturing, take advantage of FMECA more regularly, in the case of lean because any waste is reassessed and marked for elimination during short production sprints.

FMECA is excellent for asset management because it allows you to:

  • Grade potential failure and downtime severity. It's not just about what might fail first, but also what is likely to happen when that asset does break down.
  • Perform maintenance earlier, with more targeted work, on the most critical equipment.
  • Avoid as many similar issues from happening again because faster, appropriate maintenance means a critical problem doesn't have a chance to worsen.
  • Solve headaches and misdirection with a maintenance team spread across multiple sites and disciplines. Everyone has a clear sense of what to do first and why it matters.

A thorough analysis points to a failure mode i.e., the systemic or preventable reason that your asset performance suffers. It could be rust, a breakage, a leak or any definable degradation. Think of this as the slight annoyance that holds you back from asking a friend for a coffee date, because they tend to flake or bring up their ex every time.

That failure mode has corresponding, quantifiable effects on the business as a whole and other asset classes. In short, with FMECA, you have a firm idea of what to maintain, how to achieve that maintenance and which tasks have the largest impact on safety and commercial value.

RPN and criticality analysis

We'll show you how to calculate equipment criticality soon. But, as a quick tangent, we should mention the risk priority number (RPNs). They might be your preferred method for finding criticality scores — as long as you have enough data to use them with reasonable confidence.

An RPN calculates the criticality of three factors:

1) The severity of potential risks.
2) How often these issues tend to occur.
3) How well you're able to detect those defects.

You can score each of these on a 1 to 5 or 1 to 10 scale based on your maintenance reports and ongoing tracking over months or years. The full formula is:

Risk priority number = severity x frequency x detection

Anything with the highest score is deemed to be first in line for maintenance before failure is due to occur. They're your diciest investments, straining the most to stay functional. Let's hope they're worth it!

Severity can take many forms and will depend on how the asset functions within your processes. Trace maintenance costs, lost revenue, downtime periods and energy consumption for a firm idea of how severe disruption might be.

Probability is fairly easy to measure as well, using your mean time to failure (MTTF) and mean time between failures (MTBF) metrics. These tell you how frequently an asset will break down, on average, in a given period and whether that frequency is rising.

Detection, however, is trickier. Many businesses don't have accurate or up-to-date detection logs, at least in terms of when the problem occurred versus when it was identified. If you have advanced maintenance management software, it's far simpler to find accurate detection stats, but if not, then the third part of the equation becomes guesswork. For that reason, it could be simpler to skip RPN, if only to begin with.

What does sound asset FMECA look like?

Alright, we're getting close to the full review treatment: putting you in the hot seat while assets explain why you're made for each other. Before we get into the specifics, here's what helps your criticality analysis stand up to scrutiny and stay successful:

Strong reports

How are you determining what equipment fails and how often it breaks down? Do your maintenance teams conduct regular checkups or simply just react to issues instead of preventing them? A computerized maintenance management system (CMMS) goes a long way in ensuring you have a constant view of asset status, inventory and any performance tests that are due. It's often the deciding factor between good or bad data.

Excellent component knowledge

A failure mode is impossible to find unless your technicians know how the asset works. From engines, belts and motors to sprockets and springs, the maintenance team must draw effects from each cause of failure, recording their findings in accessible logs. Again, a CMMS solution is perfect for the job, because it lets the specialist add their findings to a digital, centralized hub.

Design and process awareness

Similarly, you need to have a grasp of the asset's design flaws, i.e. whether cause for downtime is expected or unexpected thanks to how the machine has been assembled. Don't discount a solid understanding of your processes, either. Reviewing the severity of reliability issues rests on linking one failure to a business outcome to ascertain whether there's a direct loss or mild impediment to other processes.

An emergency response plan

Some assets are bound to fail out of the blue, and when they do, it's wise to give technicians enough guidance for rapid repairs that must be done with an eye on safety and potential reasons for the outage (e.g., an overloaded circuit or water damage). Have emergency plans ready, including relevant manuals, photos, diagrams, troubleshooting tips and contacts for extra help, if necessary.

Got everything in place? Awesome. Let's look at the most basic equation for performing a criticality analysis.

How to carry out your criticality analysis

We mentioned RPN earlier, and the less intimidating spin on risk mitigation is almost the same. All you have to do is remove the "detection" variable.

That leaves us with a calculation of:

Asset criticality = severity x frequency

As we've explained before, score both variables on scales of either 5 or 10, with higher scores for more severe or frequent failures. This builds a criticality matrix — a chart that grades low, medium and high-priority risks on set criteria. On a 1 to 5 scale, the criteria might be:

Score 1 - 4 (low risk)

Score 5 - 9 (low-to-medium risk)

Score 10 - 14 (medium risk)

Score 15-20 (medium-to-high risk)

Score 21+ (high risk)

Assemble your scores in a table and color code them, moving through green/yellow/orange/red for every bracket that's more critical. There! You have a very basic criticality analysis dataset. It's the foundation for scheduling preventive maintenance more sensibly. Prioritize deep or light red assets, leave orange and yellow assets as your second and third priorities and focus on green assets last.

Wherever possible, use maintenance logs and investigations to discover failure modes. If you don't currently have any of this information, make time with your technicians to walk through every critical asset type, listing potential damage that can afflict the system. The four most common causes of failure are:

  • Corrosion.
  • Erosion.
  • Fatigue.
  • Overload.

From here, it's a matter of finding the right solutions to help form best practices which your team can take forward for future maintenance tasks. With alerts for preventive maintenance as well as digital access to supplementary details, they'll have a workflow that stays accurate and never leaves them lost for answers.

So, maybe some of your old favorites are soaking up too many resources or actually less valuable than you assumed they were. The opposite might be true, of course: You have more data, context and comparability to treat them with additional care when the moment calls for it.

Either way, MicroMain's CMMS is an essential step in criticality analysis. Our incisive platform watches over every asset you have, automating maintenance requests in the perfect order, preparing the right people for what's ahead. Book a demo and see where our software can take you. It just might be a new favorite, too.


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