Is There A Best Maintenance Strategy? 5 Maintenance Strategies Compared
When selecting a maintenance strategy, we can confidently say that being proactive is better than being reactive. However, it is a big decision and there are a handful of viable proactive maintenance strategies to choose from.
They vary in complexity, effectiveness, and implementation cost – so you do not want to make this decision without understanding what each brings to the table.
Is there such a thing as the best maintenance strategy? The short answer is no. The long answer is given below as we compare key characteristics, differences, and application scenarios.
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Where is your maintenance department right now?
If we looked at maintenance strategies in isolation, we could objectively say that prescriptive maintenance is the way to go. It is the most accurate strategy, it requires the least amount of staff to run, and it gives the best results in terms of equipment performance, availability, and uptime.
Unfortunately, that is not how the real world works. Companies have different maintenance budgets, use different assets, have workers with different skill sets, and have different starting positions. Let’s focus on the latter for a minute as the most overlooked factor.
Over the years, advancements in sensor and IIoT technology facilitated the evolution of maintenance strategies.
Going from left to right, each subsequent maintenance strategy brings additional benefits. Likewise, it also carries additional costs and complexity. Because of that, it is hard to jump two or three steps ahead. If you are stuck in a reactive mode, it is very challenging to make a successful transition right to predictive maintenance.
The journey is going to be much smoother if you follow the natural evolution of these strategies. Before making a decision, each maintenance department should consider where they are right now – what are their current limitations and capabilities.
For those that are determined to take a bigger jump – make yourself a favor and start with a pilot project.
Criteria for choosing the most effective maintenance strategy
Could we find an organization where preventive maintenance is an ideal strategy for all of its assets? Surely, but that’s uncommon – and the reason why a universally best maintenance strategy cannot exist.
Applying the right strategy to each asset requires a thorough understanding of:
your assets (their failure modes and maintenance requirements)
your capabilities (budget, skills, access to tools and technology)
maintenance strategies (how they work, their pros and cons, implementation costs and requirements)
In the next section, we will focus on the third point. We will briefly explain how each strategy works and proceed to evaluate them based on the following factors:
set of our preselected factors (asset reliability, work automation, ability to control costs, asset utilization, ability to optimize maintenance resources, range of applicable assets)
pros and cons
cost to implement and run
implementation requirements (in terms of skills, hardware, and software)
best used for (which types of assets)
We will include a few custom graphics to help you visualize the relative difference between those factors.
Each section will end up with a link towards an in-depth guide that discusses the respective maintenance strategy in more detail.
Comparison of five main types of maintenance strategies
Run-to-failure maintenance (a.k.a. reactive maintenance) often represents a lack of an actual maintenance strategy. It suggests that the maintenance department doesn’t have a plan – it waits until something breaks down, then sends a team to repair it. Rinse and repeat.
This approach, when applied to all physical assets, can literally ruin a business. Things start to break left and right. Maintenance teams cannot be everywhere at the same time. The deferred maintenance backlog starts to grow and operational issues become unbearable.
We just painted a pretty grim image. However, a run-to-failure maintenance strategy should not be completely discarded.
Nonrepairable assets like light bulbs and assets that are near the end of their life cycle can just be replaced after they break down. They can justifiably be on a run-to-failure maintenance plan.
Furthermore, maintenance departments operate with limited budgets. They often do not have enough resources to proactively maintain the whole facility. Still, they should be careful when choosing which assets will be on the run-to-failure maintenance program.
Additional factors to consider:
Cost to implement and run: no initial costs, very cheap to execute.
Implementation requirements: there are no notable requirements (even though it can still benefit from using a computerized maintenance management system).
Best used for: non-repairable assets, low priority assets that are cheap and easy to repair or replace, simple assets you plan to replace after their next failure.
Preventive maintenance (a.k.a. preventative maintenance) is the simplest and cheapest proactive maintenance strategy. It gained prominence as businesses realized it is more cost-effective to invest in regular maintenance than wait for assets to break down – and deal with all the negative consequences that come with unplanned downtime.
There are two types of preventive maintenance, based on how the maintenance activities are scheduled:
calendar-based maintenance (changing the filter every couple of months; changing the oil every three weeks)
usage-based maintenance (after X amount of working hours; every X production cycles)
These two types simultaneously represent the strongest and weakest sides of preventive maintenance programs.
Regular maintenance ensures the assets are kept healthy. However, this can lead to excessive maintenance – like replacing parts that could still be used for a while. Fortunately, organizations can leverage asset history, maintenance logs, and other CMMS data to keep excessive maintenance at acceptable levels.
Additional factors to consider:
Cost to implement and run: low to medium cost; the cheapest proactive maintenance strategy.
Implementation requirements: proactive maintenance culture, CMMS or equivalent system to manage maintenance work and ensure availability of spare parts, workers that are trained to perform preventive maintenance tasks.
Best used for: any asset that can cause operational problems if it fails; any low and medium priority assets that are expensive to repair or replace.
Condition-based maintenance (CBM) takes a step forward by introducing condition monitoring technology into the mix. It uses vibration analysis, ultrasonic testing, infrared testing, and other techniques to assess the current condition of an asset and its components.
That information is then used to create more efficient maintenance schedules.
The problem CBM tries to solve relates to the way wear and tear accumulate. Depending on things like input materials, environmental conditions, and machine operator behavior, the same type of assets will deteriorate at a different pace.
Instead of following a fixed schedule, maintenance managers can rely on condition monitoring data and the P-F intervals to schedule work based on the current condition of the asset.
Additional factors to consider:
Cost to implement and run: medium cost; depends on the type of condition monitoring technology the organization has to purchase.
Implementation requirements: condition monitoring equipment, CMMS, trained workers that know how to utilize condition monitoring technology.
Best used for: any medium or high priority asset which failure modes can be easily tracked with CBM equipment.
A predictive maintenance strategy is a more accurate version of condition-based maintenance. It uses condition monitoring data, OEM recommendations, maintenance logs, and other data to build algorithms that can predict equipment failures.
The model is based on predictive algorithms supported by machine learning. The more data it has, the more accurate the model is in predicting failures. This is why it needs to be continually updated.
The end goal of predictive maintenance is optimizing the usage of maintenance resources. By knowing exactly when a certain part will fail, maintenance work can be scheduled and planned for well in advance, simultaneously avoiding excessive maintenance and preventing unexpected equipment downtime.
Additional factors to consider:
Cost to implement and run: high initial costs with high potential ROI over time.
Implementation requirements: various software and hardware solutions, condition monitoring sensors, predictive analytics, specialized training in data science and predictive modeling.
Prescriptive maintenance strategy represents the most advanced approach to asset maintenance.
RxM does not stop at predicting potential failure. It relies on machine learning and artificial intelligence to build prescriptive algorithms. These algorithms not only predict failure – they offer potential solutions for the potential problems they identified.
Dan Miklovic from LNS research explained it great in his post:
Let’s say a piece of equipment is showing increasing bearing temperature. Predictive analytics looks at the temperature profile and tells you it is likely to fail in X amount of time. On the other hand, prescriptive analytics tells you that if you slow the equipment down by Y%, the time to failure can be doubled, putting you within the already scheduled maintenance window and revealing whether you can still meet planned production requirements.
Additional factors to consider:
Cost to implement and run: very high upfront costs with the highest potential ROI over time.
Implementation requirements: same as predictive maintenance, just with an added layer of complexity.
Best used for: critical assets; highly automated systems with a lot of condition and performance data.
We threw quite a lot of information at you so far. We know it is hard to juggle everything in your head at the same time. Below are some side-by-side comparisons to remedy that.
The purpose of the above image is to show the relative difference between different maintenance strategies in terms of specific factors.
For example, resource optimization shows how predictive maintenance allows maintenance planners and managers to allocate and use their maintenance resources more efficiently than if they are running reactive or preventive maintenance.
Keep in mind that the graphs do not include other important factors like implementation cost and requirements. We discussed those in the earlier sections.
Applying the right maintenance strategy to each asset
So, what is the best maintenance strategy for asset X? It is a common question and it often leads the conversation in the wrong direction.
A much better question would be: How can we address these specific failure modes that asset X has?
Every complex asset can fail in multiple ways. Scratch that. Every component of every complex asset can have multiple failure modes.
Let’s take a conveyor belt for example. Drive motor can overheat due to inoperational fan. The gearbox can fail when gear tooth damage accumulates due to abrasion or corrosion. Driveshaft bearing can malfunction due to excessive loading, corrosion, lack of lubrication, or numerous other reasons. The belt itself can slip because of insufficient tension.
Not all failure modes are created equal. They vary in the level of damage they can do, how quickly they can be addressed, how expensive they are, and what is their chance of occurring in the first place.
Selecting the right prevention methods for identified failure modes (or technology to predict them) is easier said than done. A potential solution comes in the form of reliability-centered maintenance.
Performing Reliability-centered maintenance (RCM)
Reliability-centered maintenance is a structured maintenance process that helps identify which maintenance methods will work best for each piece of machinery. It is focused on improving the reliability and functionality of critical assets in an efficient and cost-effective manner.
The RCM analysis is based on identifying potential functional failures, failure root causes, and the severity of their downstream effects (which is basically an FMEA analysis). But it doesn’t stop here. Its framework helps you select the most appropriate prevention methods.
Ultimately, it helps you build the most effective maintenance schedule for the analyzed piece of equipment.
Each failure can have a multitude of negative effects like increased labor costs, equipment damage, productivity decrease, etc. which can be quantified in terms of lost $$. When you know how much you stand to lose from a particular failure, it is much easier to decide the amount of resources you should invest in preventing it.
The solution can be applying any of the maintenance strategies we discussed above – from using sensors and analytics to track deterioration to actually letting the failure happen and being ready to fix it.
Keep in mind that RCM is a complex process that feeds on maintenance data. If you are purely reactive, don’t have a CMMS, and your maintenance logs are a mess, your organization is probably not ready to run RCM. Start with preventative maintenance and move your way up.
Performing Risk-based maintenance (RbM)
Risk-based maintenance is a maintenance process that helps you determine the most economical use of your maintenance resources. It helps divert resources from non-critical to critical assets. This is especially helpful when working with a limited budget, something most maintenance and facility managers can identify with.
The criticality of an asset is determined using a risk (a.k.a criticality) matrix. Each asset is assigned a Probability of Failure (PoF) and Consequence of Failure (CoF) factor. You can use these to map each asset on the criticality matrix. You should get something like this:
A representation of a criticality matrix
Same as RCM, RbM also relies on relevant maintenance data to ensure each asset is assigned the right PoF and CoF factors.
Naturally, the most critical assets ought to get the most attention. As such, it is easier to justify the investment into condition monitoring and predictive technology to keep an eye on your highest-priority assets.
While in some cases that might be redundant, you can technically use RbM to identify your critical assets, and then pull those assets through the RCM process to select prevention methods and create the maintenance schedule.
no access to required technology (CMMS, predictive/prescriptive analytics)
old assets that are hard and expensive to retrofit with specific sensors
lack of intra-organizational knowledge to use new technologies (or even perform complex reliability techniques like FMECA, RCA, and RCM)
poor organizational culture that is stuck in a reactive mindset
Most (if not all) of these challenges stem from tight maintenance budgets. Top management is not going to have a sudden change of heart. Maintenance managers need to work with what they have.
As a low-cost option, preventive maintenance is still the best strategy for moving away from reactive maintenance. It is fairly easy to set up and doesn’t require a lot of training. Most importantly, the implementation can be spread out in small increments. This allows the organization to adjust the speed of transition according to its capabilities.
The best maintenance strategy is NOT the one that’s best on paper. It is the one you can successfully implement and run.
Use Limble CMMS to create a single maintenance calendar for all assets
Regardless of the strategy, everyone needs a clean maintenance calendar to plan and schedule maintenance work. There are too many moving parts to do everything manually.
A sample of a maintenance calendar inside of a Limble CMMS
When the assets you want to track are entered into its database, you can use CMMS software to quickly set up all preventive tasks. You will also be able to manage incoming work requests, change task priorities, reschedule and reassign specific tasks, and track exactly how much maintenance resources are you spending on each asset.
With all of that data readily available, you’ll be able to improve upon initial maintenance schedules. You might even consider switching maintenance approaches for specific assets and failure modes.
If you already have the software implemented, the basic steps to create the maintenance calendar are:
Ensure all assets you want to track are entered into the CMMS database.
Double-check that basic asset information is correct and up-to-date (like installation date, location, and attached manuals).
Create the preventive schedule for each asset based on its maintenance history, identified failure modes you want to prevent, and other data you were able to gather.
If you are using CBM or predictive analytics, you will have to integrate the incoming data with your CMMS software (older CMMS solutions usually do not support that). After that, you will have to play around a little to set up alerts and the automatic triggering of work orders.
Occasionally review available maintenance data to see if your maintenance schedules can be improved and if everyone is following outlined procedures.
When all of that is done, you can open the maintenance calendar to overview the maintenance schedule. You can just drag and drop tasks to quickly change due dates and reschedule work. Technicians assigned to affected tasks will immediately get an email and push notification informing them about the change in priority. Likewise, they’ll be notified about any new work that was just assigned to them.
If some of the work at your facility is outsourced to vendors and OEMs, you can give them limited access to Limble CMMS and send them PMs and work requests throughout the software. This means you can keep everything in a single maintenance calendar, as well as track maintenance costs associated with each vendor.
Don’t let the fear of failure be the reason why you can’t move forward. One great thing about all of these maintenance strategies is that they can be rolled out in stages. And it is much easier to stay on top of expenses when you can control the pace of implementation.
World-class production needs a world-class maintenance team equipped with the right tools and technology. This doesn’t happen overnight. Still, most organizations that commit to a proactive maintenance culture and follow the natural evolution of maintenance strategies can eventually get there.
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