The Maintenance Maturity Model

Transcript

Hey, everyone. Welcome to the maintenance hero summit. My name is Rick Boggs, and I am so excited to talk to you about the maintenance maturity model, a road map to downtime zero. Just a little bit about myself. I'm the VP of product here at Limble. And before I joined, I was in the same shoes as many of you. I served as a preventative maintenance coordinator at Monterey One Water, a wastewater treatment facility where I administered our CMMS program, working with plant operations, maintenance managers, and technicians to drive efficiency and reliability for our organization.

Before that, I worked as the facilities management systems analyst at California State University, Monterey Bay, helping to improve workforce efficiency and business processes.

So I've had my fair share of challenges balancing urgent equipment repairs, scheduled maintenance, and the pressure to keep operations running smoothly.

Today, I'm gonna walk you through the maintenance maturity framework that helps us understand how teams evolve from firefighting to proactive maintenance, minimizing downtime, and maximizing your asset reliability.

So why does this all matter in the first place? Every business that relies on equipment or machinery has a maintenance strategy, even if it's not been consciously developed.

Simply choosing to run to failure is a strategy, although perhaps not the most effective one.

Most organizations spend over eighty percent of their maintenance time reacting to equipment breakdowns. This approach has big consequences.

There's a cost where unplanned downtime cost manufacturers millions of dollars a year on an average of two hundred and sixty thousand dollars per hour in lost production.

Not to mention the high cost of emergency repairs that require expedited replacement parts, overtime labor, and often result in collateral damage to other components.

Safety.

Not only that, emergency fixes increase the risk for technicians and operators. When machines fail unexpectedly, technicians rush repairs, and this is where most maintenance injuries can occur.

Then there's efficiency. Without structured maintenance, assets wear out faster, leading to reduced lifespan and higher replacement costs. Maintenance maturity is the journey of transforming from chaotic reactions to data driven confidence. Not every company needs to reach the highest level, but knowing where you stand helps you make smarter maintenance decisions and allows you to right size your maintenance strategy moving closer to that vision of downtime zero, where machines are available when you need them at the lowest possible cost.

The framework that we're gonna explore today has five distinct stages. We'll start at reactive, where maintenance is performed only after a breakdown.

We'll move towards preventive to extend equipment lifespan through scheduled inspections and maintenance activities.

Then we'll move on to condition based maintenance where we monitor the actual asset health and usage.

To predictive, which uses real time data to forecast failures, and finally prescriptive, the stage where your systems not only predict, but tell you the ways in which to optimize performance leveraging AI and advanced analytics.

Every organization has assets at different stages, and not all assets need to be maintained at the highest level of maturity.

Each days has their own benefits and challenges and applications. So let's go ahead and break this down.

Reactive maintenance is step one. This is where the majority of teams begin, fixing equipment only after it breaks down. It's commonly referred to as a firefighting mode.

It's simply having no maintenance strategy. In some cases, this approach is ideal and referred to as run to failure. But in many cases, it comes with its challenges and disadvantages.

It has lower initial costs due to no upfront investment.

It requires no time for resources to plan and schedule tasks, and it's just a straightforward approach.

Problems are fixed as they arise, but this has its challenges.

Higher long term cost due to potential collateral damage, emergency repairs, and unplanned downtime, unpredictable equipment failures that lead to interruptions in operations and possible revenue loss. It shortens equipment lifespan through repeated failures and increases the safety risk for operators and employees.

And overall, just reduces that asset performance and utilization over time. Now there are assets that you want to apply this strategy to. For example, a light bulb. It's not replaced until it's burnt out. So there's plenty of spare parts, and there's no preventative maintenance that needs to be, done on them. Preventative maintenance is stage two. This is where maintenance is performed regularly and proactively to keep our assets running efficiently.

It helps us reduce the likelihood of failures and extend equipment lifespan through regular inspections and maintenance activities.

Now there's plenty of advantages to this. It It can help us reduce downtime by preventing unexpected equipment failures and operational disruptions.

It helps us extend equipment life through regular care.

It enables cost savings, avoiding expensive emergency repairs and replacements in the long run. It increases our safety by minimizing the risk of equipment malfunction that could endanger workers, and there are challenges. It requires additional upfront costs and investment in resources, training, and the system setup can be high. It can also lead to possible over maintenance based on poorly planned schedules.

It requires dedicated personnel and time for these routine checks, and schedule maintenance can temporarily hop, equipment operations if they're not planned and coordinated effectively.

And this also can be complex to schedule out all of the preventative maintenance tax tasks to ensure that they're done on time and correctly.

Now there's two types of preventative maintenance. We call time based maintenance and usage based maintenance. Time based is when these schedules are occur at a regular interval.

Example, you know, every once a month.

And a usage base is where they are triggered based off of a specific usage benchmark, like every ten thousand miles or a hundred cycles.

Many organizations stop at preventative maintenance. They may not have the technical resources or expertise or budget to move on to this next stage of condition based maintenance.

It's this stage where organizations want to understand how they can optimize their existing PM programs by adjusting the schedules and the activities performed.

The next stage is condition based maintenance. This is where we are monitoring the actual condition of an asset via inspections or sensors determine when maintenance needs to be performed.

It's only carried out when specific indicators may suggest that there's a decrease in performance or there's a likelihood of failure or that the usage has met a specific threshold.

Now the advantages of this is that it can cause it can minimize the disruptions.

It can reduce the amount of costs associated with failures and emergency repairs.

And it can increase reliability, operational uptime, and worker safety.

This really allows us to opt optimize our maintenance schedules beyond these standard structured intervals and beyond what the OEM is suggesting.

Now the challenges with this is that you may have higher upfront sensor and setup costs, may require additional expertise and staff training in order to install these and set up the appropriate triggers for when maintenance should be performed.

And it can be limited for certain types of assets.

There is also the inherent risk of some sensor failure where data is not being transmitted to your system. And scheduling can remain unpredictable since it's not happening at a standard interval. So you need to be able to have the right amount of staffing to go out there and investigate an issue when a condition is flagged.

As companies invest further in sensors and monitoring equipment, an immense amount of data is now being captured, which we can analyze to better understand why something failed and what conditions it was in before it failed.

The next stage is predictive maintenance. This maintenance strategy uses data analysis and advanced technologies like IoT, AI, and machine learning to monitor equipment conditions and predict potential failures, which enable timely repairs to prevent unplanned downtime.

The advantages of this is that it can minimize the maintenance time that is needed.

It increases our uptime by ensuring that we are preventing unplanned downtime by addressing these issues before they cause failures.

This continues to improve our cost savings by reducing production interruptions and spare part expenses, and it can extend our asset life by identifying and addressing minor issues early, ensuring that we're able to prolong the lifespan of the equipment. The challenges of this is that there are high initial costs. It requires a large investment in sensors and analytics software and IoT infrastructure to get this information collected.

It can be a complex implementation to integrate these technologies.

And it requires specialized expertise and staff training.

Ultimately, this also can rely or create an overreliance on technology where we may be at risk of ignoring ignoring other failure indicators due to system reliance.

Now getting to predictive maintenance is generally the holy grail for large organizations that manufacture goods.

They need to ensure that there is the highest availability of their machines by preventing downtime on their most critical assets.

And oftentimes, it is a challenge for organizations to fully achieve this level of maturity due to the high costs of technology and staffing required.

The final stage of the maintenance maturity model builds on predictive maintenance as it uses data analysis and machine learning not only to predict when if, when to perform maintenance, but define the specific actions and maintenance that is required in order to make that equipment perform better. The advantages of this is that it delivers specific actionable maintenance recommendations.

It can reduce unnecessary repairs and costs and automates decision making for technicians.

Now the challenges are that it's still an emerging technology. It requires advanced analytics and and significant investment. There's complex integrations with existing systems, and it's limited by the data quality and the sensor coverage of these assets. So this requires a high level of expertise, and trust that the systems are interpreting the data correctly and providing accurate recommendations.

And this level of maturity is naturally the hardest for organizations to achieve. There's no single solution that is enabling you to reach this level of maturity today.

That's where creating an ecosystem of trusted technology can help. This framework provides organizations with a structured methodology to enhance asset reliability and optimize maintenance activities for maximum efficiency.

But each maintenance strategy within this framework serves a specific purpose. We must recognize that no single approach fits all of your assets.

Even for organizations that are striving for the highest levels of maintenance maturity, some assets remain the best suited for a run to failure strategy or a standard interval of preventive maintenance.

The goal here is not to apply a uniform maintenance approach to every asset, but in ensuring that the most critical and high priority assets receive the right level of attention and care. Adopting higher stages of the model requires an array of tools and technologies and expertise to deploy them wisely and understand the information produced.

So this is where, again, partnering with an experienced maintenance management solution is key.

So where do you think your organization sits on this journey? A simple assessment here can help you identify where your organization stands on the maturity model. By establishing a baseline, we can help you measure your improvement over time and identify gaps and opportunities for you to adopt new maintenance tactics and technologies.

Here are a few key areas that you can evaluate when assessing your organization.

This can be the overall maintenance strategy. How's your team primarily handling equipment maintenance?

What technology are you using?

What tools does your team currently use to manage your maintenance tasks?

And data utilization.

How do you collect and utilize your maintenance data today?

You can also assess how you monitor your asset performance, workforce management, and inventory management.

The Limble team has created a really cool self assessment tool that you can use as a framework to spark internal discussions and prioritize the next steps for your team.

This is going to be available to you after this event concludes. And we'll make sure to send this to you via email along with the session recordings.

So once you have a grasp on which stage your business falls in, it's much easier to figure out how you can move up the maturity curve. And remember, you don't need every asset at the highest level. Focus on where it delivers the biggest return on investment.

And as we wrap up, let's make sure we bring it back to the big picture.

The maintenance maturity model is more than just five stages. It's a roadmap to operational excellence.

If you're in a reactive mode, you're not alone. Most organizations start here. And if you're doing preventive maintenance, you've already taken a big step forward.

Moving towards condition based and predictive strategies isn't the app isn't about adding complexity. It's about building smarter, data driven systems that free your teams up from constant firefighting.

And while prescriptive maintenance may feel futuristic, every small improvement you make today brings you closer to that vision of downtime zero.

I know how challenging it is to shift away from reactive chaos, but I've also seen the payoff when you take that first step, whether it's digitizing your work orders, optimizing your PM schedules, or starting to collect sensor data. Your path to downtime zero doesn't have to be overwhelming.

So here's your call to action.

Assess your current maturity using the framework we share today.

Pick one or two high impact initiatives.

And leverage your CMS and emerging technologies to automate and optimize where it makes sense.

By understanding where you are on this maturity curve, you can take the practical steps to reduce unplanned downtime and move toward downtime zero.

Every stage you progress means less downtime, safer operations, and a maintenance team that can lead rather than react.

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