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7:33 pm
April 13, 2017
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Develop a ‘Profitable’ Reliability Strategy

Maximizing operational profitability requires maintenance and operations to approach reliability, efficiency, and profitability from a common strategic plane.

Maximizing operational profitability requires maintenance and operations to approach reliability, efficiency, and profitability from a common strategic plane.

Automation systems have primarily been focused on using real-time control to improve the efficiency of industrial operations. But, as process- and logic-control technology and techniques have advanced over the years, control strategies have improved significantly. As a result, plant assets are being pushed harder than ever before—something that’s had an understandably negative impact on their performance and reliability.

The effect of all of this, said Peter G. Martin, Ph.D., of Schneider Electric, Foxboro, MA, is that companies are now paying much more attention to and driving advancements in plant maintenance. Over the past two decades, traditional responsive maintenance has evolved to include preventive, predictive, and prescriptive strategies. According to Martin, while the results have been promising, some in the industry are beginning to realize that improving business performance requires maintenance and operations strategies that collaborate much more than they now do.

“If the ultimate objective is for both maintenance and operations to maximize operational profitability,” Martin wrote, “approaching reliability, efficiency, and profitability from a common strategic plane is essential. This collaborative approach is referred to as profitable reliability.”

randmDeveloping a profitable reliability strategy might seem daunting, but some fairly simple steps can help move industrial operations in the right direction. Martin outlines them here:

• Identify the critical equipment assets that represent the largest opportunity for performance improvement. Those units will frequently be found among your rotating equipment, since mechanical movement tends to wear them out over time.

• Determine what process and condition measurements are required to perform a complete asset-performance analysis. At the base equipment level, this can be a relatively simple exercise. The goal is to measure the maintained state of the equipment (how it is operating compared with its optimal operating condition) and the probability of failure over a specified time.

• Install the appropriate measurement on the asset. Typical process measurements, along with condition measurements, provide substantial reliability information. For example, the amount of process output based on a given energy input might decline as the asset nears failure.

• Use the process and condition measurements to calculate the asset’s maintained state and its probability of failure.

• Use the process and condition measurements, in conjunction with business data, to determine how much the asset contributes to real-time operational profitability. The goal is to maximize that profitability over a given time.

• Determine how much operational (control) freedom each asset has. For example, is the only operating action to turn the asset on and off or is it possible to operate the asset at a less-than-maximum level?

• Develop an asset-control scheme that includes integrated reliability and process-control strategies that maximize operational profitability. These strategies might include reducing the output of the asset to extend its time to failure so you can finish a run or a contract.

• Move the reliability measurement and control up to the next-level asset set (for example, the process unit) and perform the same control-strategy analysis. This analysis should be simpler to perform once the base equipment level assets are under control.

• Continue this process all the way up the asset hierarchy, until you have real-time control strategies in place for all your critical assets and asset sets. This would include process areas, plants, and even enterprises. MT

—Jane Alexander, Managing Editor

Peter G. Martin, Ph.D., is vice president, Marketing and Innovation, for Schneider Electric’s Process Automation business. For more information, visit Schneider-electric.com/processautomation.

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