Condition-based maintenance (CBM) might be the most expensive approach to maintaining a given asset, but overall, the payoff may be worth it. For example, if you have rotating equipment that could provide a continuous stream of revenue, you have three choices when it comes to maintenance policy. The easiest approach is fail-based maintenance (FBM) or running the equipment until it ultimately fails. Unfortunately, this leads to unscheduled production downtime, loss of revenue, and potentially catastrophic impact (e.g., safety, environmental, costly equipment damage).
A second approach, use-based maintenance (UBM), relies on periodic maintenance such as oil changes every 4,000 hours of operation or monthly filter replacement. This approach can be sub-optimal as maintenance may be too frequent or not frequent enough depending on production and environmental factors. Thus CBM, the third maintenance policy alternative, may be ideal if the benefits of corrective action outweigh the cost of tracking asset condition and predicting failure.
CBM is based on the theory that equipment is operating efficiently when measurements of vibration, heat, pressure, tension, speed, alignment, and so on fall within an acceptable bandwidth. As the equipment wears, measurements drift beyond established control limits, and maintenance is required to bring the equipment back to optimum operating conditions.
In this way, equipment failure can be predicted, so that steps can be taken to prevent production downtime and more costly emergency repair. In some industries, predictive maintenance can also prevent incidents. In environments where equipment is run around the clock, use of predictive technologies and a CBM program is essential. This is because unlike many FBM and UBM routines, predictive technologies can be used to monitor and even control asset condition while it is still running.
Some companies use outsourced predictive maintenance services for more specialized equipment such as HVAC. This is because contractors can hire more skilled people that are trained and focused on leading-edge predictive technologies. As well, third-party contractors can purchase sophisticated software, hardware, and measurement devices to achieve the necessary economies of scale. These factors are what make a CBM program cost-effective.
The advent of cloud-based internet services has further enhanced the benefits of contracting predictive technologies. For example, equipment sensors or programmable controllers right on your shop floor can be accessed online by third-party service providers. Alternatively, diagnostic and analysis tools can be accessed remotely via the vendor website.
Predictive Technologies
There are two components of a CBM program: (1) data collection and analysis, and (2) maintenance work required as suggested by the data. Many options are available in terms of predictive technologies to accomplish these tasks. Data can be collected automatically using permanent, online metering devices, or using hand-held or mobile equipment operated by in-house or external technicians. Data is then dumped into a predictive software package for interpretation. Trends are plotted by the software showing the extent and type of deterioration. Expert systems can assist in making sense out of the complex barrage of data collected, by determining the possible causes of deterioration and suggesting a strategy for dealing with the problem.
Many CMMS vendors can interface their software with the data collection and diagnostic components of specialized predictive software packages, in order to generate maintenance work orders. Examples of specialty software includes tracking and analysis of pipeline integrity, road conditions, and sophisticated lubrication analysis. More advanced CMMS packages can be used to manage a CBM program without the need for any specialized software.
Three of the more common techniques used in a CBM program are described below.
Vibration Analysis. What does it mean when your steering wheel begins to vibrate while cruising down the highway at 55 mph? Excessive vibration is one of the more common ways to predict equipment failure. Some experienced mechanics claim that just by listening to the hum or feeling the pulse of the equipment each day, they are alerted to impending mechanical problems. A more sophisticated approach is to compare actual meter readings with optimal values of frequency, amplitude, and phase to determine what problems are likely occurring.
Vibration analysis is used primarily on rotating equipment such as motors and turbines to determine shaft misalignment and bearing wear. Vibration analysis can also be helpful in monitoring the condition of common assets such as compressors, blowers, and pumps.
Lubrication Analysis (Tribology). What would you think if a few weeks following an oil change, your car's oil was black? Your interpretation would depend upon whether you owned a new car or an old one, what type of lubricant you use, the operating conditions of the vehicle, and so on. This complexity is precisely why expert systems are used to analyze and interpret the results of a variety of tests on lubricants. These include viscosity, total acid and base numbers, flash point, and quantity of particulate in the lubricant.
Viscosity relates to the ability of the lubricant to reduce friction created by moving parts. Maintenance costs are minimized at some optimal number of oil changes, corresponding to an acceptable range of viscosity readings. Total acid number determines the level of oxidation of the lubricant, whereas total base number relates to the lubricant additives. Measuring flash point reveals the extent of fuel dilution of the lubricant.
The quantity of particulate in the lubricant is probably the most important measure, and there are a few tests that have been developed to determine this. One of the more sophisticated methods is using vision systems to collect the data, and computers to compare digitized photographic images from the camera with "acceptable" images stored in the computer. Deviations from the standard image are graphed for trend analysis and then interpreted.
Another method of measuring the quantity of wear particles in lubricants employs a thin metallic film placed in the lubricant flow. As the wear particles bombard the film, it erodes thereby increasing its electrical resistance. The resistance of the film is therefore directly proportional to the quantity of particulate, and in turn, wear on the equipment.
Infrared Analysis (Thermography). When the temperature meter in your car dips toward the danger zone, what do you do? All equipment has a normal operating temperature range. Exceeding that range suggests corrective action should be taken. There are more sophisticated ways of monitoring the temperature of equipment than the thermocouples used in automobiles. Infrared cameras can take a heat snapshot of the equipment, showing different colored temperature bands. Any abnormal heat patterns, trends, or quantitative temperature values (i.e., hot spots) must be analyzed and interpreted.
Common problems detected by this technique are excessive friction on rotating equipment, leaking steam traps, damaged ovens or furnaces, and electrical overload situations.
Proactive versus Reactive: Finding the Right Balance
Finding the optimal mix of FBM, UBM and CBM maintenance policies is not easy. In a highly reactive maintenance environment, the resultant fire-fighting mentality favors FBM. On the other end of the spectrum, excessive UBM can be overkill or less than optimal. Finally, CBM may appear optimal, however, following a cost-benefit analysis may not be worth the added expense.
Overall, those that manage to find the right balance can see significant improvements, such as:
- a significant reduction in total downtime,
- a lower inventory of spare parts required in stores,
- increased production capacity as fewer machines lay idle or in the shop,
- less space requirements for spare parts and equipment that are down,
- fewer rush orders required,
- fewer quick fixes and less mistakes made,
- improved utilization of maintenance staff,
- less overtime required to respond to emergencies,
- less stress with a planned shutdown,
- better yield and less scrap, waste, and rework, and
- more predictable and stable production scheduling so that customer responsiveness is improved.
One further complication in finding the right balance is that predictive technologies are becoming less expensive as technology in general improves, which changes the point of optimal balance. Sometimes the best way to determine the optimal point is on a trial-and-error basis. A CMMS is a useful tool to build an accurate equipment history and provide comprehensive analysis capability. With a realistic history, users can balance the cost of replacing the equipment, with different maintenance policies. A CMMS could help calculate the total cost of downtime and the cost of poor quality as part of the optimal balance calculation.
