Enhancing Your Predictive Maintenance Program with Condition Monitoring
Condition Monitoring offers impressive ROI and the ability to minimize production, safety and regulatory problems
Equipment failure can be expensive, and potentially catastrophic. Unplanned production downtime, missed contract deadlines, costly machinery replacements, as well as safety problems, environmental concerns, and regulatory violations are all potential consequences of a maintenance program that fails to predict and monitor equipment problems.
Instituting a full-featured predictive maintenance program using condition monitoring (also known as CM) can help minimize unwelcome surprises, yielding an impressive ROI. Logging live equipment condition data on a regular basis through a CM routine offers plants a more scientific approach to managing equipment performance. Plants go to great lengths to understand production processes. It makes sense to apply the same rigor to understanding equipment critical to those processes.
Typically, plants that have developed effective predictive maintenance programs using CM discover that monitored assets rarely cause unplanned problems or downtime. This freedom from emergencies allows maintenance departments to address back-burner issues that can improve the overall condition of the operating assets even further. Smooth operation also improves the morale of maintenance technicians.
The initial implementation of CM usually uncovers many small, hidden, subtle problems. Resources are needed to address these issues, and, at first, the existing maintenance budget may appear inadequate for the task. But once initial problem stabilization occurs, a predictive maintenance program soon starts to recoup its initial costs. As the maintenance team gains a more thorough knowledge of the condition of its productive assets, the rate at which new problems appear declines even further, and the program starts paying dividends. The initial outlay required to purchase data collection equipment and train personnel will generally more than pay for itself after one or two key machinery “saves.”
Enter the OEMs
Collecting data on a routine basis enables technicians to identify trends and thus anticipate imminent machine failures. With advance notice comes sufficient time for planning corrective actions.
Although most organizations see the need for routine CM, many do not have the in-house resources to operate a monitoring program cost-effectively and efficiently. Often the staff members who collect and analyze the machinery information are also responsible for the day-to-day operations and spend much of their time handling emergencies. Running data collection routes to gather information for long-term trending inevitably is a lower priority than repairing a failed part that’s holding up production.
In some plants there is only one person trained in vibration analysis, which clearly becomes a problem when that person retires or transfers to another position. Even when experts stay on board, it is increasingly difficult for them to stay abreast of the skills needed to accurately interpret the reams of collected data.
To address these issues, major OEMs are filling the maintenance gap, offering their end-user customers enhanced product service and operation expertise through CM programs. OEMs have developed their expertise through monitoring and evaluating their own equipment, understanding processes and competitor systems, and partnering with condition monitoring hardware and software vendors. With monitoring programs, OEMs provide plant maintenance groups with crucial information about the health of their machinery — from performing vibration and temperature analysis to fully instrumenting equipment during manufacture, to oil sampling, thermography, and monthly route collection using ultrasonic flow measurement.
All rotating equipment can benefit from routine monitoring. Decisions about how often and to what degree monitoring should occur depend largely on criticality, cost and accessibility. Critical, high-dollar, un-spared equipment would likely call for full instrumentation to allow continuous monitoring and protection. Most other plant equipment can be covered adequately with a monthly data collection monitoring program.
The return on investment
How can plants best measure the success of a routine condition monitoring program? One of the easiest methods is to track the average cost per work order on the rotating equipment. CM programs are designed to detect potential failures before they become catastrophic. Clearly, using predictive maintenance to prevent failure will cost less than maintaining the equipment after it has been seriously damaged or compromises safety or regulation standards. With CM, there should be fewer emergency work orders and maintenance activities can be better-planned.
Each machine “save” that was a direct result of the CM program can be logged by a plant reliability engineer who assigns a monetary or other value. The value is generally determined by estimating the maintenance cost (had the equipment run to catastrophic failure) and subtracting the cost of the repair. If the “save” prevented losses due to downtime or lowered production output or avoided a safety or environmental issue, those additional and significant savings must also be calculated.
Using industry averages to compare maintenance savings with the cost of a monitoring program (see Figure 7), plants can expect payback in as little as one month. These quick returns can be used as supporting evidence when approaching upper management about incorporating CM and a predictive maintenance program into the budget. OEMs or industry partners can provide this type of supporting data.
Applying the rigor of condition monitoring in a predictive maintenance program offers a wide range of benefits, and plants employing such a program can achieve excellent long-term results. Combining CM and predictive maintenance with the use of asset management, other equipment management, and procurement applications and services can provide an extremely positive ROI.