Clearing the Data Hurdle for Effective Asset Performance Management

Few in the utility industry today disagree with the notion that technical advances in terms of sensing and analytics are yielding powerful new solutions for asset performance management (APM) and predictive maintenance. Many would also agree, however, that there are challenges for utilities ready to digitize their asset management program. Indeed, finding, consolidating, mapping, cleansing, and storing the data from a multitude of sources can seem like a daunting challenge.

Best practices are emerging as major utilities take the APM plunge, and meaningful benefits to holistic APM strategies are now clear. One transmission operator, for example, has avoided five major transformer failures since the implementation of its APM program—and said that “just one or two saves paid for the system.”

With growing emphasis on reliability from regulators, aging infrastructure, and accelerating workforce retirement at utilities, the need for a utilitywide APM program has never been greater. Understanding the data challenges utilities are likely to face is an important first step to putting a plan in place.

Who, What, Where, When, and Why?

When preparing to deploy an APM solution, the five Ws should be asked in the context of company assets and data:

• Who: Which operating divisions house data needed for the desired analytics? What institutional knowledge is held by which actors? How can it be incorporated into the APM system for preservation? How do IT and operational personnel coordinate efforts?
• What: What datasets exist today? In what format? Electronic or paper-based? Is the data accuracy good? Is it verifiable? Are there new datasets that need to be developed?
• Where: Where has asset data historically been housed? Where should it be stored going forward? Do I need a data lake? Can I store my data in the cloud? How should the transition be orchestrated? Is there data available in the field that is not communicated to the operations center? Should asset analytics be performed centrally or in the field?
• When: How often should asset data be updated? Is there connectivity to the asset, allowing for real-time or on-demand reads?
• Why: For what applications do I need this data? For what applications might I want the data in the future? What are my primary goals for the APM system—reducing maintenance expenses with proactive repairs and replacements? Reducing outage frequency/duration? Shoring up grid stability where solar penetration is high and growing? All of the above?

As the APM planning team drills down into each of these questions, new questions will become apparent. Testing and validation of analytics algorithms must be thorough and must be completed on an ongoing basis—rather than one and done. As new data becomes available, adjustments may be needed due to previously unforeseen situations.

Is It Worth It?

It’s still early days in the APM world, but clear benefits have been reported by utilities that have done pilots or full-scale deployments. As more utilities invest in APM solutions, it seems likely that the benefits—in terms of avoiding unnecessary repairs, preventing outages, averting capital investment, and efficiently managing field crews—will become apparent. New applications that can be created with a robust, agile APM platform and complete, quality datasets will also emerge.

Join the Webinar

If you’d like to learn more about the nitty gritty details of the APM world, attend the Guidehouse Insights webinar, The Digital Future of Asset Performance Management. Join me, ABB’s Matthew Zafuto, and FirstEnergy’s Dana Parshall for an interactive discussion of the data challenges and lessons learned in FirstEnergy’s implementation of ABB’s Asset Health Center solution.