by Dr. Siri Varadan, UISOL
Ensuring that an asset performs to its full potential throughout its life is fundamental to effective asset management. Various factors make this objective difficult to accomplish, however. Tight budgets, vying priorities and a strict regulatory regime pose constraints that force utilities to do-more-with-less. Utilities are, as a result, shifting their thinking and moving to a paradigm where:
- Risk is no longer avoided, but managed;
- Costs are no longer minimized, but optimized; and
- Performance is no longer maximized, but adjusted to achieve thresholds.
In the context of electric utilities and ongoing smart grid efforts, this shifting paradigm means that asset management needs to be understood in terms of the following simple high-level questions: What work should be done? When and how do you do it correctly? While these questions are simple, they provoke thought on a variety of subjects throughout the asset management process shown in Figure 1. Going through the asset management process and focusing on the correct work answers the question: “Where should a utility invest its money to obtain the best return?”
Asset management, at a high level, addresses the following questions:
- What assets does the utility own?
- Where are these assets?
- How important are these assets?
- What is the condition of these assets?
- What is the performance level of these assets?
- Are these assets’ conditions and performances satisfactory?
- If not, should action be taken to restore the asset to its original performance or health?
- If yes, what are the proper actions and how do you choose from a diverse set of actions so that corporate objectives, including customer satisfaction and regulatory approval, are satisfied?
While the first two questions almost sound trivial, they are fundamental to asset management and may be addressed by the implementation of a geographic information system (GIS) or an asset registry. A common thread in all of this is the availability and use of quality asset data.
Common sense dictates that the “squeaky wheel gets the grease.” An asset that is of consequence should get more attention. In a recent asset management survey conducted by UISOL, released in May, utilities equated the word consequence to loss of revenue, system reliability and performance. Consequence may also be understood as the impact caused by the absence of an asset on the system, the customer, other assets and socio-economic factors. Risk is one of the better measures of asset criticality because it describes the impact of the failure of the asset by combining probability of asset failure and impact. Depending on the factors considered in its calculation, risk may take various forms–operational risk, environmental risk, public safety risk and so on.
Asset criticality in the electric utility industry is typically calculated per asset or by asset type and prioritized based on the asset’s geographical and topological location. Figure 2 shows an example of asset prioritization for a utility with transmission assets. Value refers to the total sustainment expenditures and risk is a measure of the asset’s loss consequence. To clarify, the loss of an asset in the category P1 has the greatest business impact.
Asset health is often considered subjective. All factors that determine asset health are not quantifiable and, hence, asset health is different from asset performance. Despite this, several efforts are used in the industry to quantify asset health. A score from 0 to 100 is sometimes used with the understanding that 0 means the asset is at end of life and requires immediate attention, repair or replacement. A score of 100 means the asset does not need attention for the next several years.
As a starting point, asset health can be conceived as a weighted average of several components, which is a measure of an attribute of the asset that could potentially lead to failure or result in a situation that could cause a failure condition. The asset health indicator should allow peer comparison, provide a sense of remaining life and indicate how soon intervention is required to avoid failure.
Identification of failure modes and the effects of these failure modes is important to health determination in reliability centered maintenance (RCM) analysis. Failure modes effects and criticality assessment (FMECA) focuses on evaluating a failure’s impact. In doing so, a reliability engineer might focus on addressing failure modes that bear higher consequence. To eliminate human experts’ subjective variations in asset health when selecting the weighting factors used to compute asset health indices, it is best to rely on statistical data and RCM studies that establish failure rates for each failure mode.
Asset performance is a quantitative concept and correlated to asset health. The nature of the correlation, however, is a topic of further study. At a simple level, one might ask: How well is an asset performing with respect to its peers? The same question might be asked when comparing performance with other assets at other locations, perhaps owned and operated by neighboring utilities. As a result, it is important to understand benchmarking and utility best practices. It is also important to understand the role and nature of standards in evaluating asset performance.
Several measures for asset performance exist. These measures are mostly based on failure frequency and duration. Other metrics commonly used include restoration time, maintenance costs and time between failures. Financial metrics such as replacement costs, O&M costs and return on investment may also be included. Selecting and defining the metrics to use, and the logistics of data collection for calculating metrics are important when implementing an asset management project. It is difficult to calculate an individual asset’s performance due to the lack of monitoring. It is possible, however, to make valid inferences about asset performance by considering data from a variety of sources. This is typically an area where data integration helps the most.
Data collected through online monitoring of electrical and non-electrical devices is common with smart grid. This new data can be used to assess asset health and performance when the systems are integrated effectively.
Actions that restore problem assets to their original performance and health are necessary. These actions or projects could include asset maintenance, repairs, refurbishments or replacements. Each action has its pros and cons. Understanding the cost of these actions and their benefits over time is important when deciding which projects to implement. This science of decision making is at the core of asset investment planning (AIP).
Integrated AIP tools can assist in decisions making using a combination of objective functions, as well as constraints. AIP takes a list of projects and prioritizes them according to an established set of objectives. The rankings indicate projects’ importance, their expected return and the time frame in which each project must be executed. AIP also provides information about risk associated with each project.
Asset management is a cradle-to-grave concept that requires careful asset planning, operations, maintenance, performance measurement and corrective actions to improve and maintain performance. Asking the right questions along each step of the asset management process is the best way to ensure goals are met. Internalizing the responses to each of these questions will enable a utility to transform to the new paradigm. A question can have more than one correct response. It is important to ensure that the answers work in concert to achieve asset management’s overarching goal of identifying the correct work.
Present efforts at asset criticality, health and performance assessments combine data from various sources to provide quantifiable metrics that provide a sense of remaining life, when to take action and which action yields the most benefit. Correctly performing the work requires incorporation of best utility practices, tight integration of online monitoring, implementation of an asset management culture and personnel training. Leveraging smart grid efforts will be a key factor in the future of asset management.
Dr. Siri Varadan, PE, is vice president at UISOL, an Alstom company, where he leads the asset management practice. Dr. Varadan holds bachelor’s, master’s and doctorate degrees in electrical power engineering. He specializes in asset management for electric utilities with a focus on T&D systems. He is a senior member of the IEEE and a member of the Institute of Asset Management.