Asset Reliability a Performance Indicator

Feb. 12, 2014
The methodologies for managing assets to ensure reliable performance first began to be developed by the airline and power industries and the U.S. military in the 1970s.

The methodologies for managing assets to ensure reliable performance first began to be developed by the airline and power industries and the U.S. military in the 1970s. Over the past 15 years, an understanding of the value of asset reliability as a plant performance issue has spread to all industries.

Many universities began offering programs in reliability management over the past decade, and graduates are now entering leadership positions in operations and maintenance at many companies. They’re realizing that their plants are not executing the reliability methodologies they learned in school. When they experience too many failure events and issues, they recognize that this can’t go on.

Industries with an active interest in asset reliability include the oil and gas, chemical, refining, pulp and paper, power, metals and mining, and food and beverage industries. Reliability is often one of their top three business objectives.

Rank Assets for Criticality

Any reliability program must begin by ranking assets for criticality in terms of the potential impact of their failure on plant production. Strategies then need to be developed to ensure the optimal performance of these critical assets and extend their operating life.

Finally, decisions must be made about what technologies and what data to use to determine asset health. Some examples include when and how often to measure motor vibration or motor stops and starts, or whether to use wireless vibration sensors or wireless mesh networks, which make it easier for companies to get data from assets in places where it’s difficult or dangerous for humans to reach.

How Work Gets Done

Having the right people resources and assuring they have the right skills or adequate training is another important aspect of reliability management. It’s also essential to understand how work gets done in a plant. It takes multiple people with different skills and properly documented work orders that provide them with an understanding of what went wrong and what tools are needed to fix a device.

Often a process needs to be improved, streamlined and documented to improve asset reliability. You also need really good KPIs such as availability and return on asset value, and the ability to communicate all the findings in a work management system.

Smart devices that can diagnose their own health and provide in-depth process information are key to improving asset management. With more network or wireless connectivity, more information has become actionable. Software lets you analyze performance and detect a problem long before it begins, so that an operator or maintenance technician can be alerted to take action.

Getting the Right Balance

The combination of the speed of technology change, the growth of automated systems and the decline in the number of plant personnel with the experience and skill set to maintain those systems is causing problems for manufacturers in all industries. One automation supplier conservatively estimates that 75 percent of all plants are running sub-optimally. Systems are always degrading; even valves have moving parts.

The first step in addressing the issue is to get the right balance between predictive, proactive and reactive maintenance. There is no magic number, no strict definition for what is a good balance. Although most people will say that keeping reactive maintenance at 20 percent or lower is optimum, the right service schedule depends on how critical an asset is to plant and process performance, as well as company objectives in terms of variability, cost and equipment wear.

Condition-based maintenance that allows you to repair or replace only what’s needed, vs. trial and error work based on historical schedules, can save a typical plant hundreds of thousands of dollars in costs and thousands of man-hours every year.

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