Scott Stukel, CMRP, Director of Asset Management and Reliability at Total Resource Management

I had a question recently posed to me regarding Optimization of Preventive Maintenance Activities for Calibrating Instruments. I wanted to re-post the topic here along with my response in case any of you have any input or questions.


How can Preventive Maintenance activities for the Calibration of Instruments be optimized, assuming that the legacy/current state is that there are defined time-based frequencies for calibrating them? What methods may be used to evolve from time-based to condition/performance based calibration?


Yes, calibration has traditionally been performed on a time based schedule. This can be problematic on both sides, if the instrument falls out of cal before the interval is reached it can result in negative safety, regulatory, quality, or business/financial consequences. If you calibrate too often it can not only result in more work and higher cost, but can also impact instrument life. So the optimum solution falls in determining the business driver and desired benefit/outcome, taking into considering risk.

If you determine that benefit is worth it and the risk is acceptable of altering the method of determining when instrument should be calibrated, then you can employ a different practice to improve. By leveraging your EAM / CMMS system as well as device data/IoT analytics you may be able to determine not only candidates for modifications to calibration routine, but also let the data and data analytics help monitor condition & performance to more dynamically adjust the approach. One technique may be to use your EAM / CMMS data to shorten/lengthen the calibration interval when you see that either instruments are being calibrated that don’t need it yet (extend cal frequency) or if you find that they are grossly out of cal when you calibrate them and may have been that way for some time (reduce cal frequency).

A better way may be to utilize device / IoT data to monitor for instrument or process/product anomalies and trigger the calibration event. For example, you may be able to trend instrument output, compare to nominal standards, and detect threshold violations at the moment they happen. You may also find that condition or quality parameters in process or product output may trigger the need to calibrate. These are only a few methods that may help solve your challenge. I hope this helps and let me know if there are any comments or questions.

This question and more are discussed in our closed Asset Management/EAM Live Forum LinkedIn Group. If you have any feedback or would like to learn more please reach out to me on LinkedIn.