Let’s face it: In life, in business, it doesn’t make a whole lot of sense to start your day by doing yesterday’s work. This adage holds especially true in heavy industry, where maintenance strategies can range from reactive to proactive.
Maintenance is at the very core of the heavy industrial sectors that build and power our world. For several decades now, generations of industrial operators have poured a ton of sweat into finding the right balance between performing too much and too little maintenance on their machines.
It’s a time-honored test. But why is it still such a fine line to walk? Let’s take a look.
Pop quiz: Do you know the criticality of your assets?
Under-maintain your assets and you run a greater risk of failure. Over-maintain them and you waste precious time, money and resources — all of which quickly add up. What’s more, the best solution to the problem changes based on your answer to this question:
What’s the criticality of your asset?
To measure criticality, calculate your risk per asset. The risk of an asset is the likelihood of it failing multiplied by the consequence of it failing.
From there, you can build a risk matrix of your assets. Organize it by increasing chance of failure (i.e. rare, remote, unlikely, seldom, occasional, likely) and increasing severity of failure (i.e. incidental, minor, moderate, major, severe, catastrophic).
Your maintenance strategy should be different based on those varying levels of criticality.
For example, it probably makes sense to use condition-based monitoring software on a critical centrifugal pump to study its signal data and better understand its unique operating health and behavior. You’d want to know about any anomalies early on, before they turn into catastrophic failures. Odds are, you’d choose to make the necessary pre-emptive repairs to stop future failures from happening.
However, it doesn’t make sense to use the same strategy for a light bulb. The criticality and cost of the bulb are low enough that you can simply and safely run it to failure, then replace it.
Obviously, the above scenario is starkly contrasted. And truth be told, the reality is that the vast majority of a maintenance team’s time is spent somewhere in the large gray area in between. But at the end of the day, the principle is really that simple.
Are you leaving money on the table with your current asset maintenance strategy?
More likely than not, the answer is yes. But have no fear: Even the best and brightest maintenance practitioners and reliability engineers are in constant pursuit of solving this challenge.
Only once you’ve properly assessed the criticality of your assets can you pick the right maintenance strategy for each individual piece of equipment.
Here are a few methodologies to understand and consider:
- Very high criticality: Reliability-Centered Maintenance (RCM) — Ensuring that your assets continue to do what they’re intended to do, leveraging maintenance and monitoring as tools to support the end goal of increased uptime and improved reliability.
- High criticality: Failure Modes and Effects Analysis (FMEA) — Identifying potential failure modes for key asset components, and documenting those causes as well as their effects on the rest of the asset.
- High to medium criticality: Preventive Maintenance Optimization (PMO) — Choosing the right preventive maintenance tasks and intervals to perform, to balance the risk of failure and the cost of maintenance — a continuously improving exercise.
- Medium criticality: Standard care — Overseeing the basic care procedures for a particular asset, such as inspecting, cleaning and lubing.
- Low criticality: Run to Failure (RTF) — Running the asset to exhaustion, then replacing it with a new one.
With your risk matrix in place, you can take steps to financially optimize your maintenance strategies and get the most bang for your buck, which this post covers.
Wouldn’t it be great if there was a database that could help you make better decisions for all things maintenance?
You’re in luck: Now there is!
Uptake’s Asset Strategy LibraryⓇ (ASLⓇ) is the world’s largest database of industrial asset types, failure modes and maintenance tasks. Think of it as a guidebook of best practices on what to do — and what not to do — when it comes to maintaining your equipment assets.
Remember the balancing act described earlier in this post? The ASL and related software tools simplify the decision-making process by bringing a vast amount of data and subject matter expert knowledge to the table. Users are just a click away from gaining valuable insights covering:
800+ asset types.
58,000+ universal failure models spanning all known operating contexts.
5,000+ preventive maintenance (PM) tasks and intervals organized by operating context.
178,000+ as-found reportable conditions.
32,000+ human working years of professional industry experience.
What does it ultimately mean in terms of outcomes?
The ASL has proven to be effective in helping businesses reduce their maintenance costs by an average of 30% compared to traditional PM strategies, and in helping them improve their reliability by an average of 20% as measured by Mean Time Between Failure (MTBF).
Or, in other words: Getting the reliability you need at a price you can afford.
What’s MTBF and why is it important?
MTBF is the average time between failures of an asset during its course of operation. It’s an industry-standard metric that professionals track in order to better understand how long an asset is capable of operating without interruption. Knowing the MTBF of an asset helps teams plan accordingly for expected repairs.
It comes as no surprise that maintenance strategies play a pivotal role in improving MTBF by proactively addressing issues before they turn into bigger problems. But MTBF can also be improved by conducting root-cause analysis to determine why certain components fail in the first place, then working backward to mitigate those root causes where possible.
The same goes for using condition-based monitoring tools. These tools are incredibly powerful because they help technicians know the right maintenance tasks to perform at the right time based on the actual needs of the individual asset in its unique operating environment — as opposed to relying on time-based intervals or generic guidelines from Original Equipment Manufacturers (OEMs), which are often warranty recommendations and potentially lead to overspending on maintenance.
Want to learn more? Check out this customer case study to learn how Uptake saved $10 million for the largest nuclear-generating site in the U.S. by improving asset performance and lowering maintenance costs:
