Though the idea of preventative and predictive maintenance has existed for some time, it was previously restricted by the limited information available to maintenance engineers who provided advice on machine health status. Additionally, temperature and vibration sensors were placed to check for anomalies on certain assets.

Over time, predictive maintenance has developed into a whole new approach to its core. Modern systems, which rely less on traditional sensors, harness the power of artificial intelligence and big data to provide a holistic view of asset risk, imminent failures, and perform automated detection of fugitive emission leaks with little the need for a human operator’s judgment.

Predictive has a variety of uses, including predicting the remaining usable life of an asset, diagnosing fugitive emissions hot spots, detecting partial faults, and continuously monitoring safety/security parameters through on-site telemetry.

At WH Consulting, we have successfully created and installed an algorithm using regression analysis and predictive analytics to determine where fugitive emission leaks could occur. Our unique Predictive Leak Modeling Software (PLMS) can help save you time, money, and even emissions. Using key performance factors for each component we can now use the data to tell us where the potential leaks are more likely to occur. Predictive analytics has a plethora of applications.

However, the vision that it gives the reliability and integrity group is unparalleled. With key data points and data tags for all the components in the database, R&I groups can make better decisions on future purchases. Leveraging past performances to determine future purchases places the power of controlling your cost while getting maximum performance in your hands.