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Speed Up Machine Failure Diagnosis

EP Editorial Staff | May 10, 2020

These five tips will help you better predict, diagnose, and manage asset failures.

By Bryan Christiansen, Limble CMMS

The ability to quickly identify causes of machine failure often is the difference between a productive day with all targets met and a day of wasted raw materials, labor, time, and lost revenue. Here are five tips you can use to speed up machine-failure diagnosis.

Maintain accurate equipment history.

Every effective maintenance program is based on successfully executing a pre-established maintenance plan. No plan can succeed without accurate background information. When equipment malfunctions, performing an accurate failure diagnosis can be almost impossible without reliable information about the history of that machine. This applies to any asset but can be particularly useful in the case of recurring failures. Of course several other factors play a role in this process, but adequate records about an asset from sources such as OEM manuals, technicians who have worked on it in the past, and operator feedback will shorten the time it takes to determine the cause of the failure.

Use preventive-maintenance checklists.

We all know the main benefits of preventive maintenance. However, what many don’t realize is that preventive-maintenance checklists can also facilitate equipment-failure diagnoses. The logic behind this is simple. If everyone is performing the same routine maintenance actions, the number of reasons for machine failure becomes limited. That results in less time that a technician has to spend troubleshooting. Of course, this only works if all maintenance technicians are actually following the steps outlined in your PM checklists.

Use of mobile maintenance software.

These days, maintenance technicians can easily use a mobile device to check equipment logs for a machine and receive additional support from the rest of the team, if needed. This way, the diagnosis can be performed on the spot (without searching for and pouring through paper records), resulting in a faster repair process. Because of this, and other advantages, mobile maintenance software has become a valuable tool for building efficient maintenance workflows.

Implement condition-based monitoring.

Since quick failure diagnosis is a priority, it makes more sense to leverage a system in which specific parameters (heat, vibration, noise) are used to monitor the health of an asset by connecting it to condition-monitoring sensors. Based on predetermined failure modes, this setup triggers alerts that allow the maintenance team to pinpoint the exact problem and take action. Condition-based monitoring increases asset efficiency, eliminates failure-diagnosis guesswork, and reduces downtime.

Adopt autonomous maintenance.

Another way to speed up machine-failure diagnosis is to make maintenance a team approach. An example of this is autonomous maintenance in which machine operators are trained and then given the additional role of carrying out basic maintenance on the assets for which they are responsible. Due to their proximity to these machines every day, operators often can quickly spot and report any failure symptoms. EP

Bryan Christiansen is the founder and CEO of Limble CMMS, Lehi, UT. Learn more about Limble CMMS software at


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