Five Pitfalls in Predictive Maintenance Techniques

Many organizations have cut their maintenance costs through Predictive maintenance efforts, simultaneously improving quality, safety, reliability and productivity. Unfortunately, there are a few pitfalls into which unsuspecting organisations get into while using the predictive maintenance approach. Identifying these traps will enable you to steer clear of them and set up an effective Predictive Maintenance program.

Learning to identify and avoid the recurring traps in your maintenance program will help you to be more effective in the application of both preventative and predictive maintenance techniques.

Pitfall #1: Capital Expenditure for equipment, but not for training

When maintenance budgets are submitted, and ultimately cut down, many companies fail to provide funds for adequate training to support the new Predictive maintenance related equipment. For example, some organisations invest on expensive infrared thermography equipment, but do not provide funds for proper training of personnel to exploit the full potential of the equipment. Thus the equipment would remain as an expensive toy with very little return on investment.

While OEM training on the basic operations and capabilities of the supplied equipment is essential, investment in the right kind of training is critical. OEM vendors may provide basic how-to-use training, but this may be inadequate for the users to utilise all the possible features and further more. Training by a brand-neutral or independent trainer for a particular technique using the new equipment would be beneficial on the long run. Training more than one person is also recommended to ensure year round availability of specialists. A word of caution – Do not train and allow too many people to handle expensive equipment since accountability for
equipment faults, damage etc becomes less.

Pitfall #2: Applying one predictive technique for all situations

If the only tool you have is a spanner, then every problem looks like a bolt. For instance, if you only have a vibration analyser, would you be able to identify loose connections in an electrical enclosure? Understanding the proper application of the different predictive tools is paramount to implementing and sustaining your system. Most predictive techniques are used together to improve reliability, aid in root cause analysis and improve safety. Organizations have obtained good results using a combination of predictive techniques like contact ultrasound, vibration analysis, oil analysis and thermography on gearboxes. They have been able to cut repair costs significantly by identifying a failing component instead of replacing an entire assembly.

Pitfall #3: Failing to properly re-inspect after corrective work is complete

The above scenario occurs all too often, in far too many operations. Predictive maintenance identifies problems that usually are undetectable by human senses. If the problem could only be seen with the predictive equipment, then the same reasoning should be applied when re-inspecting it. There are many instances where a repair has left the equipment in worse condition than before. For example, corrosion develops inside an electrical connection and maintenance makes the situation worse by tightening the connection. Or, in disassembling piping to repair an air leak, mistakes are made when putting the piping back together.

Without proper re-inspection, we would have no idea of the havoc we have caused in our own system. When you are using predictive techniques to identify a problem, ensure that your system schedules a re-inspection using the same technique.

Pitfall #4: Predictive Maintenance Corrective work orders get lower priority

Organisations that haven’t made the transition from reactive or breakdown maintenance to preventive maintenance will not be very effective in adding predictive maintenance to their work strategy. Maintenance supervisors will tend to prioritize more obvious problems.

All personnel involved in the maintenance process, especially those that have been working in a “reactive” maintenance mode need to understand that predictive work orders are a priority.

Predictive maintenance replaces parts before they fail—and this is a mindset that only comes with training and practice. The savings can be tremendous when parts are replaced before catastrophic failures take place to full machine assemblies.

Pitfall #5: Lack of a supporting maintenance system

While many companies will spend enormous amounts of time and money on tools, equipment, parts and materials, they will not focus on developing the foundation of a good maintenance organisation—the maintenance system. Using predictive techniques without an effective maintenance system in place only optimizes your reactive maintenance program. It will result in marginal savings and less-than-anticipated payback. Predictive maintenance is good, but you must have the other programs in place to support it.

Watch your step

In summary, recognising and avoiding the above mentioned five pitfalls of Predictive maintenance adds substantial value to any maintenance organisation.

Adapted from an article by Mark Pond of Marshall Institute – Posted by Maintenance Technology