All Member Open Forum

How are you translating CBM data (oil analysis, vibration, particle counts) into financial language that leadership understands?

Are you linking condition monitoring findings directly to avoided downtime, MTBF improvement, or asset lifecycle cost models?

Curious what frameworks others are using to bridge technical diagnostics with business decision-making.

------------------------------
Linda Perry
Senior Business Development Executive
The Viswa Group
American canyon CA
------------------------------

Savings from a CBM program are hard to pin down, because we are talking about failure events that never actually happen. While my department does keep a list of our findings, with an associated value for each, those numbers are wild guesses and we don't normally use them for reporting or metrics. I've seen tools for calculating the value of PdM strategies, and maybe someone else will chime in here and school me on how they are an important component of a mature program, but I can't get my head around the fact that the numbers that get plugged into those models are made up. (We do occasionally report year-over-year savings for specific assets or asset classes that we have focused our reliability efforts on, but that involves more than just condition monitoring.)

I do make a point to share highlights of our PdM findings each month with our site leadership team, especially ones that affect high-profile projects or processes. It's fun to see the looks on their faces each time they realize we helped them dodge a bullet.

------------------------------
Dale Nicholson, PE, CMRP, CRL
Reliability Engineering Mgr
Evonik Corp
------------------------------

Our PDM program is primarily focused on Oil Analysis and Vibration.   We ask sites to track findings and put an estimated savings from cost avoidance.   As Dale Nicholson stated in his response,  I find this a little difficult because trying to place a value on something that didn't happen.   When working to justify a new program,  I look at failures across a production line or area then look at the cost of these failures.   By avoiding them I should see a reduction so I will commit to a 50% reduction (Under Commit and over deliver).   I can then pull this same data a year after implementation to confirm we are achieving the savings.   This naturally should translate to throughput by reducing the unplanned downtime associated with failures but I don't use this as the primary measure.   At the end of the day,  leadership wants to see results in dollars saved so that's the best methodology to present the data in.

------------------------------
Mark Pospisil
Program Manager Maintenance Excellence AN Division
Abbott Laboratories
Sunbury OH
------------------------------