Why Partial Adoption of Condition‑Based Monitoring Leads to Poor Results

Back in 1995, I was presenting at a Chemical Manufacturers Association conference when a quiet voice in the back of the room interrupted: “What a load of bull!” The slide that triggered the comment showed that the industry’s best performers generate 55 % of their workflow through condition‑based monitoring (CBM). The audience went silent, and I seized the moment to ask for the speaker’s perspective.

He described a plant that used vibration analysis, infrared thermography, ultrasound, oil analysis, motor testing and non‑destructive testing, yet CBM accounted for only 5 % of its workflow. He had 1,000 rotating machines, but only 60 were on routine vibration monitoring. I asked, “If you expanded those technologies to 60 % of your asset base, could they generate 50 % of your workflow?” He was stunned. He’d never considered that benchmark coverage model.

That lesson remains relevant: many companies expect transformative results from CBM while only “dabbling.” The most common pitfall is applying just one or two technologies across a small portion of assets.

Understanding the Fundamentals of CBM

Every piece of industrial equipment emits early warning signals—heat, vibration or sound—before failure. These signals, or failure modes, can be detected with specific CBM tools. However, equipment typically has multiple failure modes, meaning a single technology rarely captures all potential problems.

Take a chiller, for example. Vibration, oil analysis, refrigerant analysis, online/off‑line motor testing, and ultrasonic leak detection may catch many issues, but you still might miss early signs of a tube‑bundle failure. Adding eddy‑current testing—and possibly other techniques depending on material and fluid—can uncover the hidden faults. In practice, a single piece of equipment may require a dozen complementary tests.

Successful CBM programs therefore hinge on two principles:

• Identify every probable failure mode for each asset.
• Deploy the appropriate technology stack to detect those modes.

Why do organizations “dabble”? Because expanding a program demands commitment—and risk. Many prefer to experiment first, hoping to prove ROI before scaling. Unfortunately, this incremental approach rarely delivers the full benefits. Limited coverage fails to detect most problems, causing equipment to run to failure, frustrating teams and ultimately leading to the conclusion that CBM is ineffective.

Using one or two technologies on a handful of assets yields little to no payback. While you may perform a superficial cost‑avoidance analysis, the approach does not influence profitability. True ROI comes from integrating a comprehensive technology suite across a high percentage of the asset base, enabling proactive scheduling, skilled labor deployment, timely parts availability, precision repairs, and minimized impact on overall equipment effectiveness (OEE).

Adopting a piecemeal program results in an evolutionary, never‑ending process that can never match best‑practice outcomes. Achieving those results requires engineering a deliberate, full‑scale CBM strategy.

John Schultz is a Certified Maintenance and Reliability Professional (CMRP) with the Society for Maintenance & Reliability Professionals and a partner at Allied Reliability. Schultz and Allied Reliability are recognized leaders in applying CBM to build proactive maintenance models. Read more of his articles at www.alliedreliability.com. For additional information, email info@alliedreliability.com or call 918‑382‑9400.