A Complete Guide to Condition Based Maintenance (CBM)
Maintenance has been around ever since the first caveman got tired of building a new spear for every other hunt and thought to himself: “I bet there is something I can do to use this one for a longer period” (albeit less eloquently).
While those times are long past, one thing that enabled us to come up with advanced technological solutions is exactly this type of proactive thinking.
As the technology evolved and we developed wireless networks, highly accurate sensors, and powerful software analytics, the stage was set for the maintenance world to start using advanced predictive maintenance techniques like condition-based maintenance to monitor complex assets.
And the statistics reflect this trend. According to the Markets and Markets, the machine condition monitoring market is expected to grow from $2.38B in 2018 to $3.5B by 2024.
With that in mind, we decided it is time to tackle this topic by answering the following questions:
What is Condition Based Maintenance and what are its goals?
When and how to apply CBM in practice?
What are the benefits and downsides of using CBM?
What are the requirements for the successful adoption of CBM?
What is condition based maintenance?
Condition based maintenance (also known as CBM) is a maintenance methodology in which maintenance operations are performed depending on the current condition of your assets.
performance data (often gathered by different sensors/tools)
The above-gathered data shows you when a certain piece of equipment might fail so you can schedule maintenance work just before that happens.
For example, you might install a sensor that measures the vibrations of a certain piece of rotating equipment. Over time, that moving piece will degrade and start falling out of the alignment which will result in an increased amount of vibration. The installed sensor can then warn you when the amount of vibration crosses a set limit so you know that part should be replaced shortly.
Condition based maintenance vs predictive maintenance
There is a lot of confusion out there on the difference between CBM and predictive maintenance. Some people like to use it interchangeably, but that is not quite right. There is a lot of overlap between CBM and predictive maintenance, but they are NOT the same thing.
Prediction maintenance combines condition-based diagnostics (measuring vibrations, temperature, and other variables that have a predictable pattern) with complex predictive formulas to exactly predict when a piece of equipment might fail.
CBM relies on set intervals and lacks those predictive formulas that are used to interpret different trends.
So, in a way, predictive maintenance is a more accurate version of condition-based maintenance.
What is the goal of CBM?
The main goal of condition-based maintenance is to help you optimize your maintenance resources by performing maintenance work only when needed.
However, accurately predicting when something will fail is not always that straightforward. As a result, CBM brings its own set of advantages and downsides we will discuss later in the article.
Before that, we need to explain condition measurement, condition monitoring, and how you can apply CBM to your organization.
Condition measurement vs condition monitoring
To perform maintenance proactively, operators should know the state of a machine at any point in time. Thus, they need to know what is going on and use that information to determine when to intervene.
Condition monitoring makes it straightforward to achieve this objective. Condition monitoring is the process of establishing the state (condition) of an asset by monitoring specific operating parameters of the equipment. It aims to identify significant changes or deviations that are typically indicative of a developing fault.
Condition monitoring is major support for predictive maintenance.
However, to carry out such monitoring, it is necessary to take measurements at regular intervals. These measurements are called “condition measurements” and are essential for determining the condition of the asset(s) being monitored.
The collection and analysis of these measurements will reveal results that enable the accurate diagnosis of the equipment’s state. Consequently, the maintenance team can plan the appropriate maintenance actions to prevent failure and ensure the continuous availability of the equipment.
Some of the most common conditions to measure include the following:
There can be no condition monitoring without condition measurement.
Condition monitoring techniques
The measurements that form the basis for monitoring and equipment’s operating conditions are obtained by non-invasive data collection activities. These condition measurements may be collected in a non-destructive manner continuously or at intervals using transducers, sensors, and different condition monitoring tools (portable instruments).
The following are the usual condition monitoring techniques being applied:
Vibration analysis is the most commonly used monitoring technique for rotating equipment (e.g compressors, centrifugal pumps, motors). Installed vibration sensors monitor axial, vertical, or horizontal movement and send notifications when it becomes excessive.
Lubricant (oil analysis) is another non-invasive technique that can reveal the internal condition of a machine. It works by analyzing the number and size of particles (debris) such as iron, silicon, aluminum silicate, etc. in collected oil samples to determine asset wear (lubrication).
The amount of radiation emitted by an object increases with temperature. This is invisible to the human eye but is easily and quickly detected by infrared cameras. These cameras constantly watch for temperature irregularities in energized equipment.
Malfunctioning equipment generates a sound that ultrasonic sensors can detect. This technique is applicable for a very wide range of machinery, from both high-speed and slow-speed equipment to high-pressure fluid situations. It quickly alerts operators about issues like deep subsurface defects (e.g. welding defects or extensive corrosion), leaking gases, and over/under lubricated bearings. It is also ideal for specific electrical inspections especially closed gears (for safety reasons)
Though condition monitoring can play a beneficial role in your maintenance program, it’s often implemented in a rushed manner without a full understanding of some factors that will affect its effectiveness in the overall system.
This section looks at some key preliminary points to consider for a strategic, rather than haphazard, adoption of CBM.
Preliminary questions for choosing a condition monitoring solution
With the wide range of condition monitoring solutions available, it’s important to first understand your needs, then the capabilities and limitations of these solutions, before making a final decision of which one you want to use.
Consider the following:
1) Does the solution monitor specific failure modes?
A failure mode is a specific cause of the failure or one of the possible ways in which a system can fail. The more complex equipment, the more failure modes it can have.
Understanding these failure modes and their impact will help you identify and adopt the right condition monitoring solution which is an important aspect of improving asset reliability.
Some methods analyze the causes of failures and help one understand their frequency and impact. One of these methods is the Failure Modes and Effects and Criticality Analysis (FMECA). For each asset, the failure modes and effects on the entire system are calculated and recorded before generating the full FMECA.
This step is part of the initial condition monitoring process. Thereafter, the appropriate maintenance tasks for each identified failure mode can be determined.
2) Does the technology interface with existing ERP/CMMS systems?
With the continuous advancements in the way we use data, it is increasingly necessary that all your data channels can interface effectively with minimal or zero disruptions to operations.
Such channels would normally include software like Enterprise Resource Planning (ERP) and Computerized Maintenance Management System (CMMS). Some organizations may also have incorporated tools from the Internet of Things (IoT) such as wireless technology.
Whatever the case, the data stream from the monitoring sensors should work with the other systems already in place if you want to squeeze the most value out of condition-based maintenance.
3) What is the ease of implementation?
Some condition monitoring sensors and solutions are easier to implement than others. You need to understand and completely scope the resources needed to implement a specific condition monitoring solution.
Consider the time, labor, and effort required for implementation because it can be significant depending on:
4) Can alerts be generated accurately and improve over time?
Before applying a particular solution, consider how reliable the generated alerts will be.
False positives are not uncommon in condition monitoring settings and they are one reason why an organization may decide to abandon the process after implementation. If technicians are continuously called on to respond to “failures” that end up being false several times, eventually everyone will lose confidence in the system.
Therefore, check the record of the ratio of true versus false positives from your proposed solution provider. The aim is to confirm that even though these false positives may occur, they will reduce with time.
Understanding the P-F interval and the P-F curve
If maintenance personnel can find some signs or evidence that a piece of equipment is about to fail, they can take steps to prevent that failure incident. Fortunately, machinery generally exhibits warnings before they fail. This is where the P-F interval comes into play.
The P-F Curve illustrates the behavior of a machine as it approaches functional failure.
As failure begins to manifest, the curve shows that the equipment gradually deteriorates to the point where it can be detected (P), i.e. the point of potential failure. However, if failure is not noticed and mitigated, the situation continues until the system fails. This point is called a functional or hard failure (F).
The time that elapses between points P and F are known as the P-F interval. The P-F interval represents the best time for detecting and arresting imminent failure.
In condition monitoring, the interval between P and F must be enough for analysis to be effective and corrective action taken as this whole process would be pointless otherwise.
Think of it this way. Finding out that something will fail a couple of days before it happens is useless information if that doesn’t give you enough time to apply corrective measures.
Ideally, the P-F interval gives the maintenance team enough leverage to plan the right maintenance task on time to prevent functional failures. However, determining the interval between inspections can be challenging. The good news is that there are a lot of different condition monitoring techniques (we described earlier) you can use to spot potential problems on time.
A general rule-of-thumb is to set the intervals for inspection somewhere midway of the P-F interval. Or at least, the monitoring time must be shorter than the span of the P-F interval. Again, using multiple monitoring points within the P-F interval is even better and more advisable.
Establishing a condition-based maintenance program
Here is a simplified overview of how to create a condition-based maintenance program:
The best way to do this is by performing an RCM analysis and focus on the failure modes that can be managed using CBM strategies.
#3) Select the right CBM solutions and monitoring techniques
We had a whole section about this so we are going to skip details here. In short, you need to select the right solutions for the failure modes you identified in the previous step.
#4) Define baseline limits for chosen CBM solutions
You need to define acceptable condition limits so that the system can warn you when monitored equipment is starting to deteriorate. These limits have to be set in a way that you have enough time to perform corrective actions.
#5) Establish the CBM program
Running any maintenance program requires you to define tasks and responsibilities and assign them to your maintenance team. Collecting and recording measurements should be in the center of your plan.
#6) Analyze the data and act accordingly
Analyze the data coming in from sensors and inspections to plot a trend and schedule maintenance work accordingly.
Benefits of condition based maintenance
All proactive maintenance strategies bring similar advantages to the table and CBM is no exception.
Here are some notable benefits of using condition-based maintenance:
reduced number of unplanned failures
improved equipment availability, reliability, and worker safety
minimized time spent on maintenance (by doing maintenance work only when needed)
repairs can be scheduled during non-peak times
increased asset lifetime
improved equipment performance
minimizing inventory costs (you can order a part when you plan to do a repair so you don’t need to hold as much inventory)
As you can imagine, it’s not all sunshine and rainbows. Some of the stated benefits do come with a cost.
Let’s see what are the challenges of using this maintenance approach.
Downsides of condition based maintenance
Knowing exactly when to perform certain maintenance activities can’t be done by solely relying on visual inspections. That is why CBM uses data gathered from multiple sensors. Of course, these sensors first need to be bought and installed. Additionally, the staff needs to be trained to learn how to analyze and interpret all of the data that is coming in (and act accordingly).
Here is a more detailed list of challenges that come with CBM:
condition monitor tools can be expensive to install (in some cases you, need to go as far as to make certain modifications to your assets so you can retrofit monitoring equipment)
you need to spend considerable time and money to train your employees so they are able to use CBM technology effectively
sensors might have trouble working properly in harsh operating conditions, especially when trying to detect fatigue damage
working in harsh operating conditions can also damage the sensors, forcing you to replace them on a regular basis which often isn’t cheap
as you are only doing maintenance when data shows you need to, there is always a chance that multiple assets will need maintenance at the same time – this can lead to unpredictable peak times which will definitely challenge your maintenance team
Same as with predictive maintenance, the successful implementation of CBM will reduce your maintenance cost in the long term, but you have to be able to deal with the fairly high upfront cost for the initial implementation.
Requirements for the implementation of CBM
If you’ve read this article carefully, you should already have a decent grasp of what you need to have in place to successfully use condition based maintenance as your go-to approach to proactive maintenance.
But, it doesn’t hurt to have it all in one place so here is the list of things you need to have in place before you start relying on condition based maintenance:
Maintenance team that is willing to learn and adapt to the new changes in their workflow
This might seem like a lot of work, but that is the price you have to pay if you’re looking to run highly optimized maintenance operations.
If this seems too complicated and expensive, you can always start with a simple preventive maintenance plan. The transition from reactive to preventive maintenance is fairly cheap and less complicated, it can still give you comparable benefits.
Whether or not your organization is suited for implementing condition-based maintenance is something that needs to be decided on a case-to-case basis.
We hope that this article gave you enough insight to serve as a good starting point for whichever path you decide to take.
One thing is clear, reaping the benefits of proactive maintenance is the only way to stay competitive in any production environment.
April 22, 2019,
awesome content and very helpful ,very very insightful its so profound
Are you asking how we implemented those processes in Limble?
If so, I would be happy to arrange a quick demo as this is best seen in action.
Alternatively, you can go to our homepage and click on the “TRY SELF DEMO” button to play around in Limble and see how it works. That being said, the demo is probably a better option if you’re looking at how to use Limble to support a CBM strategy.
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