For many industrial operations, lubrication remains a vexing challenge. Indeed, when machine bearings fail, there’s a better than 70% chance that faulty or insufficient lubrication practices are ultimately to blame, according Ken Bannister’s “Lubrication for Industry”. Lubrication-specific key performance indicators (KPIs) can go a long way to addressing this costly problem. The key to making them work? Getting the right data from the outset.
Tracking KPIs that target lubrication gives maintenance professionals unique insight they can harness to reduce the frequency of machine failure. In addition, lubrication-based KPIs can help organizations to increase equipment uptime and productivity, enhance the availability, performance, and lifespan of expensive assets, improve maintenance efficiency, and reduce costs.
Some high-level lubrication KPIs provide a snapshot across entire operations. One of these is overall equipment health, a useful gauge of plant readiness. It shows the percentage of all equipment in a facility with no known issues or defects. Another is lubrication-related failure, which is often a simple calculation of the monetary cost, number of incidents, or other measures of equipment failures that can be traced to lubrication over a given period of time. More targeted lubrication KPIs cover such areas as lubrication program effectiveness, costs, lubrication cleanliness and quality, health and safety issues, and lubrication storage, among others.
While a number of lubrication KPIs can be generated using data from CMMS, EAP, and other generalized predictive and preventive maintenance management tools, some of the most valuable ones require data gathered at the level of the individual lubrication point. Three examples include lubrication task completion, lubrication tasks past due (backlogs), and lubrication consumption.
Lubrication task completion
This lubrication KPI gives reliability and maintenance managers a clear picture of the overall efficiency of lubrication practices at the task level. It’s a measure of the total number of completed lubrication tasks divided by the total number of scheduled lubrication tasks over a certain timeframe. A low figure may reveal inefficiencies in such areas as lubrication routes, workload balancing, resource allocation, or equipment access.
Lubrication tasks past due
This is the mirror KPI to task completion. It reflects the total number of lubrication tasks not yet completed versus the total number scheduled. A high figure here reveals similar concerns as a low task completion score. More important, this KPI, along with task completion, tells maintenance organizations how often and to what degree lubrication goals are being met.
Lubrication consumption