How to make condition-based maintenance more effective

How to make condition-based maintenance more effective

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This article is a complete guide for optimizing condition-based maintenance (CBM), including what CBM is, the different types, how it’s used and how to use it for maximum return.

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Equipment failure is not a single event—it is a process. This concept, that breakdowns are both a journey and a destination, has become firmly established in the realm of maintenance best practices. Condition-based maintenance (CBM) can act as a guide on the road to failure and back.

We’ve provided some tips, tricks and tools so you can understand condition-based maintenance a little better, use the strategy more effectively, and make your maintenance operation run like a well-oiled machine.

What is condition-based maintenance?

Condition-based maintenance is a predictive maintenance strategy where various elements of an operating asset are observed and measured over time to identify and prevent deterioration and possible failure at the earliest possible moment. Under CBM, maintenance only occurs when data indicates a decline in performance or the early warning signs of failure. This differentiates CBM from preventive maintenance, where tasks are performed at regular intervals.

The goal of condition-based maintenance is to uncover equipment failure before it happens, so maintenance can be done exactly when needed. Because CBM is based on collecting and analyzing data, it can be used to identify trends in asset performance and asses where an asset is in its lifecycle. This makes it easier to make informed decisions on everything from scheduling and labour to budgeting.

One example of condition-based maintenance is monitoring pressure readings on equipment with water systems. Monitoring pressure levels allows maintenance staff to identify when and where a leak is likely to occur before it happens, instead of at the point of failure.

When is condition-based maintenance used?

Although condition-based maintenance can be used on most assets, equipment must meet certain requirements for CBM to be used effectively.

First, as the name suggests, there must be a condition that can be monitored. If performance can’t be measured, you won’t be able to tell if there is a change in performance, which indicates the need for maintenance.

It is also crucial to be able to observe these changes in performance far enough in advance of failure so maintenance can be completed before the asset fails or deterioration affects production.

Equipment failure is not a single event – it is a process. . .Condition-based maintenance can act as a guide on the road to failure and back.

Another important consideration is the criticality of your assets. Condition-based maintenance provides the best return on investment on your most critical assets. That’s why it’s a good idea to conduct a criticality analysis to determine which pieces of equipment are most likely to fail and what impact that failure will have on your operation. If you are easing into CBM, think about starting with your most critical assets and scaling from there.

Lastly, condition-based maintenance can only be used if the right processes and systems are in place. The maintenance team must be able to capture performance data, analyze it, and make timely decisions based on the results.

What are the benefits of condition-based maintenance?

There are several advantages to using condition-based maintenance on assets, especially in a production-intensive, equipment-heavy environment. Here are a few of the major benefits that can be gained from CBM:

  • It is much easier to predict failure and fix it before it occurs, which means CBM can help reduce unplanned downtime and labour hours while increasing throughput.
  • The time between maintenance increases because repairs are only done on an as-needed basis. This means less downtime, reduced backlog, and fewer costs.
  • The likelihood of disrupting production is reduced as CBM is usually performed while assets are working and doesn’t normally require equipment to shut down for inspection.
  • If an unexpected failure does occur, using CBM can lead to a quicker diagnosis of the problem, thereby reducing the cost of breakdowns.
  • Because CBM provides an early warning system for equipment failure, you can control inventory much more effectively and won’t need as many emergency spare parts.
  • Responding to an unplanned breakdown is one of the riskiest tasks for a maintenance technician. Condition-based maintenance creates a safer workplace by reducing the likelihood of equipment failure.
  • Overdoing it on maintenance can cause equipment to deteriorate faster. CBM helps prescribe the optimal amount of maintenance for an asset, decreasing the chances of collateral damage to its systems.

Different types of condition-based monitoring

Condition-based maintenance is rooted in condition-based monitoring. This involves keeping tabs on the state of an asset using certain performance indicators. There are a number of different tools and techniques that allow maintenance teams to do this. These methods can include low-tech approaches, such as observation by a technician, or more technologically advanced processes, like gathering data through sensors.

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One of the hallmarks of condition-based monitoring is that it is non-invasive. This means measurements are taken without shutting down a machine or adjusting the way it operates. Data is collected either at certain intervals or continuously through sensors, visual inspection, performance data, and/or scheduled tests.

The following is a brief rundown of some of the techniques used in condition-based monitoring:

Vibration analysis

This type of condition monitoring identifies potential failure by spotting changes in normal vibration signature. Vibration is affected by amplitude, intensity, and frequency. Sensors can detect abnormalities in these elements, which can be a sign that something is wrong with an asset. For example, rotating equipment, such as compressors and motors, exhibit a certain degree of vibration. When they degrade or fall out of alignment, the intensity of the vibration increases. Sensors can detect when the vibration becomes excessive and the component can be repaired or replaced.

Infrared and thermal analysis

When certain parts or systems heat up past specified temperatures, it can cause them to deteriorate, warp, break, burn out, or start a fire. Infrared cameras and thermal sensors are used to determine when a piece of equipment has become too hot and alerts the maintenance team so they can take the necessary steps to fix it. Infrared and thermal analysis is frequently used on energized equipment, such as electrical conductors, and motorized parts that operate at high RPM.

Ultrasonic analysis

Ultrasonic instruments help detect deep, subsurface defects. They do this by measuring sounds that are inaudible to us and converting them to a pitch we can hear. Once these sounds can be discerned by the human ear, it’s easier to recognize anomalies in an asset and rectify them. For example, as ball bearings begin to wear out, they become deformed. This creates irregular surfaces on the bearing and increases the emission of ultrasonic sound waves. This can signal to a technician that the bearing is on its way to failure.

Acoustic analysis

Acoustic analysis is similar to vibration and ultrasonic analysis. It uses sensors and microphones to detect sounds that indicate an asset is not operating quite right. However, where the main use of vibration and ultrasonic analysis is to uncover deficiencies in rotating equipment, acoustic analysis has the added benefit of being able to target gas, liquid, or vacuum leaks. This is a key advantage for production facilities in the oil, energy and mining industries.

Oil analysis

Oil analysis helps diagnose the internal conditions of oil-wetted components and their lubricants. This method can determine the health of an asset that uses oil, fuel or coolant and whether it is nearing failure. Oil analysis can be as thorough as testing blood samples. This type of condition monitoring can include testing for dozens of different elements, such as the level of wear metals or dirt contamination in oil. It also captures information on viscosity, acid levels, water content, and more to determine the effectiveness of the oil as a lubricant.

Electrical analysis

When an electrical current is too strong or too weak, it can cause problems for an asset. Electrical analysis uses clamp-on ammeters to measure the current in a circuit. Using this tool, it’s easy for maintenance teams to gauge when a machine is receiving an abnormal amount of electricity. The piece of equipment can then be shut down and serviced before a bigger, more expensive electrical problem occurs.

Pressure analysis

In many industries, production relies on maintaining the right pressure within equipment so fluid, gas, or air can move through a pipeline or hydraulic hose properly. This is where pressure analysis can play a part. If the pressure drops in a piece of equipment, it could mean that there’s an internal problem requiring maintenance. A spike in pressure would be a sign of breakage or an imminent explosion. Conducting pressure analysis allows maintenance teams to see these changes happening in real-time and respond to them before issues spiral out of control.

Many of these forms of condition monitoring can be used together to gauge the health of an asset. For instance, several sensors can be attached to an asset that measures everything from temperature to pressure, ensuring all systems in a piece of equipment are functioning optimally.

How to use condition-based maintenance more effectively

Using condition-based maintenance is one thing. Using it effectively is a whole other story. If you don’t have the right systems, processes and procedures in place, condition-based maintenance can cost you more time, money and goodwill than it’s worth. Here are a few ways maintenance teams can harness the power of CBM and build a sustainable operation around condition monitoring.

Step 1: Map out your assets, failure modes, and baselines

It would be an understatement to say that you need to know your assets inside-out before implementing condition-based maintenance. You must understand everything about how equipment functions so you can properly calibrate sensors, spot problems as soon as possible, and prescribe the right cures.

First of all, you have to map out all your assets and their possible failure modes to understand if each piece of equipment has the key ingredients for CBM. The first key ingredient is a condition that can be monitored. Condition monitoring doesn’t work for every asset, so knowing which ones don’t support sensors or other monitoring tools and techniques can save you lots of time and money later.

Overdoing maintenance can cause equipment to deteriorate faster. CBM helps prescribe the optimal amount of maintenance for an asset, decreasing the chances of collateral damage to its systems.

For the remaining assets, determine if the failure modes identified by condition monitoring can alert you to a problem with enough time to fix it in a cost-effective way. If the answer is yes, the asset is likely a good candidate for condition-based maintenance.

Once you have your group of qualified assets, it’s important to set baselines for normal operation. Baselines are the established thresholds that indicate a healthy and fully functional system. For example, the baseline vibration frequency for a bearing may be 1000 Hz to 2000 Hz. Any number between those two frequencies means the bearing is operating at its optimal level. If it reaches above 2000 Hz or below 1000 Hz, it could signify a problem.

Baselines can be established in many ways, from manufacturer recommendations to historical trends. Creating baselines for each system takes the guessing out of condition-based maintenance and makes your decisions much more efficient and effective.

Step 2: Understand and use the potential failure (P-F) curve

Talking about condition-based maintenance without the P-F curve is like talking about a car without wheels; it just doesn’t work.

The P-F curve demonstrates the relationship between machine breakdown, cost, and how it can be prevented. It is based on the fact that equipment might be in the early stages of failing even if seems to be working fine. Along the X-axis of the curve is time. As you move through time, the machine moves from the point of potential failure to the point of actual (functional) failure. As you move through time, there are also instances when faults can be detected before total failure.

Along the Y-axis is the machine’s condition. The machine progresses from top working condition to point of failure, and then down from there until actual failure.

The most important part of the P-F curve is the P-F interval. The P-F interval is the time between an asset’s potential failure and its functional predicted failure. For successful CBM, you must ensure your inspection intervals are smaller than the P-F interval so you can catch a failure after it’s detectable, but before it actually occurs. Fine-tuning your maintenance intervals is also crucial to optimizing condition-based maintenance.

Understanding the P-F curve and the P-F interval is key to building an efficient CBM strategy. The P-F curve and interval allow you to determine how often you should complete a CBM task. The frequency of maintenance is reduced, as are the costs and time commitments associated with maintenance.

Step 3: Leverage maintenance technology

Condition-based maintenance combines recommended guidelines with repair and performance data to determine what tasks need to be completed and how often. When these parameters are decided, it’s maintenance software that can be used to help you get a jump on everything from logging sensor data to triggering work orders and scheduling maintenance.

Integrating sensor data with maintenance software, such as a CMMS, can help reliability engineers, maintenance managers and technicians capture, organize and analyze information much easier, quicker and more accurate.

Maintenance software also gives you the ability to automatically trigger a work order when certain measurements fall outside the established baseline. For example, you can set up a CMMS to schedule maintenance on a filter when the differential pressure exceeds 20psi. This way, maintenance can be scheduled at the most appropriate time, reducing the likelihood of failure while maximizing resources.

Optimized inventory purchasing is another great byproduct of using maintenance software to manage condition-based maintenance. Because software can track work order history and create reports on parts usage, it makes it easy to adjust inventory levels so you’re only ordering the parts you need, when you need them. Not only will the parts always be on-hand (eliminating downtime), but inventory prices can be cut.

Step 4: Create a solid training program for staff

While condition-based maintenance relies heavily on technology and automated systems, like sensors and software, there will always be a human element involved. For your CBM strategy to be as efficient and effective as possible, it’s vital that all members of the maintenance team are properly trained on the concept of CBM, its benefits and how to use the systems. This will increase buy-in, eliminate user error and increase reliability throughout the process.

Training should include a thorough breakdown of the different types of condition monitoring and how they affect each asset at your facility. It should also be clear how every member of the team can ensure sensor data is logged correctly and how resulting maintenance tasks should be treated. It’s a good idea to create an asset management policy at this stage of CBM implementation as it will help everyone in your facility, not only the maintenance team, understand how CBM is impacting the organization as a whole and their place in ensuring the strategy works to its full potential.

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