Using asset performance management to improve insights for process industries
Asset management comes in many different forms and can enhance insights and plant performance with the right information and tools.
Asset management insights
- Asset performance management (APM) integrates data, asset ecosystems, practices, and digital tools, evolving through five levels.
- Smart asset management and digital transformation focus on proactive data use for business value. Key drivers include reducing operational costs, speeding up market entry and empowering the workforce for efficiency and flexibility.
Asset performance management (APM) prioritizes achieving business goals as well as traditional asset reliability and availability goals, said Inderpreet Shoker, director of research, ARC Advisory Group, in the presentation “Smart asset management to realize business outcomes” at the ARC Industry Leadership Forum in Orlando.
APM is fed through four different sources to help companies achieve their business goals:
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Data and analysis. This includes digital twins, digital threads, equipment and process data, asset health, analytics and machine learning.
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Asset ecosystem. This consists of operating assets in use along with interrelated assets, plants and facilities. Production, maintenance and engineering workers all play a part in the ecosystem by gathering and reporting information.
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Practices and applications. This comes from a multitude of different best practices and philosophies such as root cause analysis (RCA), asset integrity management (AIM) predictive maintenance and reliability-centered maintenance.
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Digital tools and techniques. Digital tools such as augmented and virtual reality (AR/VR), worker connectivity devices, smart instruments and more help enhance the facility and provide a new dimension to what is being seen and done.
Asset management, like any process, is a journey where companies are trying to improve their operations and efficiency. The goal with asset management is to become prescriptive and take charge of the situation rather than being in reactive mode. Five levels were highlighted for the journey:
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Level 1: Manual processes that are reactive and run to fail.
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Level 2: Automated and planned maintenance
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Level 3: Preventive maintenance and integrated solutions.
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Level 4: Predictive maintenance, failure mode effects analysis (FMEA) and RCA.
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Level 5: Prescriptive maintenance, asset optimization and utilizing Industry 4.0.
Asset management’s evolution consists of five levels with the eventual goal of reaching prescriptive maintenance and Industry 4.0. Courtesy: Chris Vavra, CFE Media and Technology
It is one of the top industrial drivers for companies, but many companies are in different phases in their journey. Shoker said many companies are often around level 2 and working their way toward the third level and thinking about the fourth.
Asset management and data sharing requires a digital thread, she said, which can accelerate production and sustainability while being cost-effective and efficient.
Improving asset visibility, performance
Stuart Johnson, a manager of planning and scheduling for Southern Star Central Gas Pipeline, said asset management is only as good as the program and its visibility. Companies need to ask who’s responsible for the program, how they’re going to track completion and what the final report will look like.
Larry Megan, head of digital at Baldwin Richardson Foods, said smart asset management and digital transformation is about the proactive use of data to create new business value. The three drivers for this are reducing operations costs, improve speed to market and enable workforce empowerment.
Manufacturing efficiency and flexibility are critical, he said, particularly in his industry, which makes custom ingredients for food and beverage companies. “The more we make, the more we can sell in this market. It’s all about maximizing throughput.”
Steve Seiler, a modeling and analytics engineer for Koch Ag & Energy Solutions, discussed the benefits of enhancing asset monitoring in a facility by combining advanced pattern recognition with engineering principles.
Accelerating flexible production and sustainability can help companies improve their design, build, supply chain and more. Courtesy: Chris Vavra, CFE Media and Technology
He said a data science or engineering-based approach to monitoring assets is not an either-or solution. Rather, the two approaches compliment one another and each provides tangible benefits that are enhanced when brought together. Combining human understanding and intuition with advanced pattern recognition helps deliver a more focused answer and better overall results.
Chris Vavra, web content manager, CFE Media and Technology, cvavra@cfemedia.com.
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