The Asset Health Indexing in Practice
Asset health indexing software collects and consolidates data from multiple systems, analyzes the data and generates alarms as the current condition of the asset degrades to give early warning, hence signalling a potential failure.
Exelon is one of the largest competitive U.S. power generators with close to USD 27 billion in annual revenues, over USD 55 billion in assets and more than 32,000 megawatts of owned capacity – one of the cleanest and lowest-cost power generation fleets in the U.S. The ComEd division delivers electricity to several million customers in northern Illinois.
ComEd needed to enable better visibility into the current overall health of critical assets and establish a continuous fact-based capital planning cycle. They commissioned Kinectrics Inc. to conduct an asset health study of 31 different classes of substation and transmission assets.
The study developed a score for each of the 57,000 assets, where zero represented an asset that had failed beyond repair and 100 represented a brand new asset. This asset health index score was initially used to drive capital replacement plans and help prioritize maintenance work for the following year.
The study itself was quite valuable but the data volume was overwhelming. ComEd needed a way to update the indices on a fairly regular basis with minimal effort so that they could make decisions based on the current health of their assets.
The Solution to Monitor Assets
Asset health indexing software by Bentley Systems made it much easier to communicate the results of the health index analysis to top regulators and management on a regular basis. Instead of a physical report that sits on a shelf and is read by a few people, health indices are stored in a database and made available to anyone with access to a PC or mobile device.
The data can be sliced and diced in a variety of formats. A capital planner might want to see projected capital spend by year based on various risk scenarios. An engineer focusing on a particular class of equipment might want to focus on the health of assets of that class, and then drill into the details of assets with poor health.
A procurement manager might want to compare the performance of assets from one vendor versus another before making a major purchase decision. All of these users can have access to the latest data, analyse it, trend it, and drill into the details.
Bentley’s AssetWise collects and consolidates data from multiple disparate process control, SCADA, CMMS, and homegrown systems, analyses the data and generates alarms as the current condition of the asset degrades to early warning signalling a potential failure.
Automatic Calculation of Health Index
Now the automated Health Index Worksheet for each of their identified asset classes calculates the index for each asset in the asset class. For example, one health index component might be to count the number of infrared measurement problems (on a circuit breaker) over the past year. Another might be to determine the most recent trip time measurement (on a circuit breaker). A third might be to find the maximum load peak readings over the past 60 months (on a transformer).
Each component data value is normalized by referencing a factor table and deriving a factor, ranging from 4 (excellent health), to 0 (very poor health). Each factor is then multiplied by a weighing factor to obtain a score for that component. Some asset classes could have as few as 14 uniquely calculated components, while others could have as many as 90+ components, depending on the complexity of the equipment.
Next, each component score is calculated; the component score is divided by the maximum possible score to derive a health index expressed in percentage (0 to 100) for each component. Finally, all the component scores are combined and divided by the maximum possible scores to determine the overall health index for the asset/system in percentage (0 to 100).
Also a calculation is made on the data that was found during the component calculations to evaluate how complete the data was during the calculations. For example, if a health index for an asset was found to be 95 percent (quite good) while the data availability was only 65 percent (moderate) then the confidence of the health index might be somewhat suspect.
Assets in a given class can then be ranked by their health index score and the poorest (lowest percentage) identified for further analysis. The data is provided by a number of automated daily interfaces to several legacy systems, providing:
• Updates to the assets
• Indicator readings (measurements) for all the measured parameters
• Work orders (created against the assets)
• Problems identified in the field for each asset
Better visibility into the overall health
All factors, weightings, parameters, and components are maintainable and tailorable by Exelon ComEd personnel, allowing what-if scenarios to be run at will. Health indexes can be run on an asset or by the entire asset class. The developed framework and logic allows other asset classes and health indices to be easily added. Finally, the calculation programmes can be modified by Exelon IT personnel to provide a robust flexible solution into the future.
The inputs to the health index calculations are now collected automatically every night from the various source systems. The information can be augmented with manual data from Excel spreadsheets and updated indices are calculated.
By generating asset health indices in a much more timely and automated fashion, AssetWise is providing ComEd with much better visibility into the overall health of its extensive physical plant. Health indexing is bridging the gap between short-term corrective work driven by condition-based maintenance, and longer term capital planning, which used to be driven by periodic one-time studies (or last year’s budget and available capital). The foundation has been set for fact-based decisions on how to find the right balance between ongoing maintenance, capital replacement, and overall risk mitigation.
Over the years, the evolution of technology and the adaptability of the people to it, has been increasing drastically. This process has brought about a boom in the service sector, making the IT subunit of it, the most successful.
Siemens welcomes the initiative previously published by the OPC Foundation to further enable OPC UA adoption throughout industrial automation by extending standardization and harmonization activities for OPC UA, including TSN-enabled Ethernet networks at the field level. Siemens, as a founding and board member of the OPC Foundation, is a strong supporter of the OPC UA technology and has been active in core standardization working groups for many years.