Predictive Analytics: When Will It Fail?

Predictive Analytics

Asset maintenance and reliability are topics regularly covered in trade publications, around the water cooler, and in budget planning sessions. For those that walk the plant floor, however, those same terms are more often than not a reminder of a jarring phone call at 2:00 AM or a mid-day emergency stoppage associated with some catastrophic equipment failure. Anxiety from those experiences is partially tied to the knowledge that unplanned maintenance and repair costs are disproportionately high – as much as five times higher than planned maintenance. Those same experiences also came with a heightened sense of pressure and a corresponding risk of personal injury. Today’s production staff are caught in a Catch 22 when it comes to asset maintenance and reliability. Even though plant resources have become scarce, plant management’s expectations for production and profitability have increased.

Many technology vendors have approached the challenge of asset maintenance and reliability with a variety of condition monitoring capabilities. Generally, these technologies monitor one or more attributes and primarily assess the vibration associated with a given asset. The vibration data collected can be analyzed and used to gain insight into the health of an asset and/or a particular asset malfunction. Due to their high cost, however, most condition monitoring technologies are narrowly focused on rotating equipment that is deemed critical and that is capital intensive. This leaves the majority of a production facility’s stationary assets unmonitored and at-risk. Further, the limited scope of these technologies overlooks other relevant equipment data that is at the fingertips of most every process manufacturer.

Related Reading: Fix or Replace: A Sustainability Conundrum

This paper focuses on the unique benefits of predictive analytics solutions. These software-based technologies analyze multiple channels of asset data as a means of first cataloguing historical conditions and then applying that library of information to predict – and otherwise prevent – equipment failures. It analyzes other and seemingly irrelevant data to establish a complete understanding of an asset’s state. Through the use of predictive analytics solutions, plant production staff can effectively eliminate unplanned shutdowns and reallocate limited resources towards meeting the plant’s production goals. More importantly, they can do so safely.

Read the white paper, When Will It Fail? Anticipating Equipment Failure Using Equipment Analytics.

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