—W H I T EPA PER Rethinking asset performance management for the digital age at utilities — Your asset performance management strategy determines whether your assets help drive your business forward or hold your business back. In this white paper, we help asset and maintenance managers understand how a digital asset management strategy can enable the predictive maintenance needed to increase overall asset effectiveness while lowering costs. Reading time: 20 minutes — Table of contents 04 – 05 The journey to maximum value from assets 06 – 07 Choosing the right maintenance strategy 08 – 09 Overcoming unpredictability with predictive maintenance 10 The benefits of predictive maintenance for electrification distribution assetss 11 Making predictive maintenance pay 12– 13 The benefits of predictive maintenance for electrification distribution assets 14 Optimize your asset management with ABB 4r e T h I N K I N G A S S e T p e r f o r m A N C e m A N A G e m e N T f o r T h e D I G I TA l A G e AT U T I l I T I e S No matter what business you’re in, you’re in the asset management business. Without physical machinery, devices and electrical systems, asset- intensive businesses like manufacturers, utilities, refineries and more, simply don’t work. That makes asset management one of the most critical strategic functions of your entire organization. However, the world of asset management is rapidly evolving, with the emergence of the Industrial Internet of Things (IIoT) leading to the digitalization of physical infrastructure. Smart sensors embedded into assets provide massive quantities of data that can be used to fine-tune performance, measure utilization, determine return on investment and help plan maintenance actions. This asset data couldn’t have come at a better time, particularly when it comes to your electrification assets. Today’s baby-boomer dominant energy workforce is rapidly aging; as experienced asset and maintenance managers and engineers retire, much of their institutional knowledge will walk out the door with them, with no simple way of replicating or sharing that knowledge. A competitive market for talent may mean you have to rely on fewer people to do more work. Not only that, but an aging legacy infrastructure can mean that you’re spending more time and money conducting costly preventative maintenance, which may or may not be necessary based on the equipment’s actual condition. Because many of these systems are siloed from each other and require manual monitoring and operation, your limited staff time is spent collecting and analyzing data, with little time left over to take data-driven action. Unplanned downtime isn’t just inconvenient. It’s dangerous. The wrong asset failing at the wrong moment can lead to workplace injuries or fatalities to operators and service personnel. You have a moral and legal responsibility to keep workers safe. You also have a financial responsibility: the economic impact of work-related injuries and death costs global businesses almost $3 trillion¹ per year. Both the direct and indirect costs of failure are something your business cannot afford. Your asset management strategy determines whether your assets amplify or create a drag on your business results. By placing data at the foundation of your strategy, you can improve the way you approach maintenance to increase its overall effectiveness while reducing costs. ¹ https://www.safetyandhealthmagazine.com/articles/16112-ilo- global-cost-of-work-related-injuries-and-deaths-totals-almost-3- trillion — The journey to maximum value from assets T h e j o U r N e y To m A x I m U m vA lU e f r o m A S S e T S 5 6r e T h I N K I N G A S S e T p e r f o r m A N C e m A N A G e m e N T f o r T h e D I G I TA l A G e AT U T I l I T I e S The maintenance conundrum is this: Conduct maintenance too early and you may spend money and time fixing something that isn’t broken, but if you wait until it's too late you may end up damaging equipment and suffering unplanned downtime. Just like Goldilocks, the goal is to get it “just right.” Throughout the years, several strategies have been developed to determine the optimal moment to conduct maintenance in a way that provides the greatest overall availability over the long term for the lowest cost. There are two main approaches to maintenance: corrective and preventive2. Corrective maintenance is simple to understand; run the asset until it breaks, and then fix or replace it. — Choosing the right maintenance strategy While this has the benefit of saving money on unnecessary maintenance, the risk of unplanned downtime, equipment damage and employee safety make corrective maintenance unpalatable for all but the most inessential or redundant assets. For several assets, the more logical approach to maintenance is preventive. By taking action before an asset fails, you can extend the life of the asset, reduce overall total cost of ownership and avoid catastrophic unplanned outages. But the challenge, if not the art, of asset management is determining the exact best moment to conduct preventive maintenance. C h o o S I N G T h e r I G h T m A I N T e N A N C e S T r AT e G y 7 There are a number of preventive approaches: • Time-based maintenance: This approach involves conducting maintenance based on a schedule (such as every 12 weeks) or a run-time basis (such as every 10,000 hours). While this helps ensure your assets get regularly inspected and serviced, you can end up wasting time taking a perfectly working asset offline, not to mention the cost of replacing parts that may still have life left in them. • Condition-based maintenance: A more sophisticated approach to maintenance uses condition-based monitoring equipment to monitor the asset’s actual condition. This allows you to conduct preventive maintenance when an abnormal condition is detected, allowing you to get the most use out of every component. The downside of condition-based maintenance is that it can make your maintenance demands naturally more reactive and harder to predict. • Predictive maintenance: With this approach, you can use data collected by your condition- based monitoring equipment and other external sources to not only track the condition of equipment but anticipate the future performance of each asset. With this sophisticated analysis, you’ll be able to optimize your maintenance scheduling, minimize the time spent maintaining equipment and reduce costs. 22 BS EN 13306:2017 Maintenance. Maintenance terminology Indirect costs (consequence of failure) Probability of failure not under control. Highest risk of production/ service loss No maintenance, just CAPEX to restore at failure Probability of failure under control just after the recurrent inspections High maintenance costs, due to recurring equipment inspections 24/7 monitoring of data correlated to relevant potential failure causes Less maintenance costs due to reduced inspections Continuous prediction of probability of failure and remaining life Lower maintenance costs: run only when required. Direct costs (maintenance and spares) Corrective maintenance Time-based maintenance Condition-based maintenance Predictive maintenance 8r e T h I N K I N G A S S e T p e r f o r m A N C e m A N A G e m e N T f o r T h e D I G I TA l A G e AT U T I l I T I e S The majority of asset failures are uncorrelated to the age of equipment or the time between maintenance inspections; a study by NASA and the US Navy found that 82% of asset failures were completely random, with only 18% being the result of age3. Two identical assets can have wildly different maintenance requirements throughout their life, with no way of knowing how, why or when each will fail. However, many organizations still perform preventive maintenance as if maintenance frequency or the age of equipment are still the primary factors. That means a time-based maintenance strategy only provides a benefit for those 18% of assets that happen to fail “on time,” leaving the vast majority of maintenance needs unserved. While these schedules are determined using best practices, an asset will almost always fail unpredictably in between scheduled maintenance. — Overcoming unpredictability with predictive maintenance Many asset managers find that scheduled maintenance is too frequent for a relatively new asset and too infrequent for an asset's needs near the end of its lifecycle. With a predictive asset management strategy, you can continuously predict the probability of failure and remaining life for every asset you monitor. This helps you achieve the lowest maintenance costs of any strategy by allowing you to conduct maintenance only when required. According to ABB data, a predictive asset management strategy can decrease maintenance time and frequency by 30%, helping you achieve a 40% OpEx cost reduction compared to a time- based maintenance strategy. In addition, it can help you avoid costly and disruptive emergency services since activities can be planned before failure occurs. 3 https://reliabilityweb.com/articles/entry/reliability_centered_ maintenance_report_by_f_stanley_nowlan_and_howard/ Equipment Maintenance Time-based Predictive MV circuit breaker Visual/Basic 2h every 3 years 1.4h every 4 years Advanced 2h every 5 years 1.4h every 6 years MV switchgear Visual 0.5h every 2 years 0.35h every 3 years Basic 0.75h every 5 years 0.5h every 6 years Advanced 2.5h every 10 years 1.75h every 13 years 100%PREDICTION AVOID HIGH COSTLY UNPLANNED LABOR 30%DECREASE MAINTENANCE TIME + 30%REDUCE MAINTENANCE FREQUENCY + Maintenance savings in terms of lower duration and frequency thanks to predictive analysis. — Source: based on ABB experience. 1 0 0 % 9 10r e T h I N K I N G A S S e T p e r f o r m A N C e m A N A G e m e N T f o r T h e D I G I TA l A G e AT U T I l I T I e S While most of electrical distribution assets have no moving parts, these devices are some of the most important and hardest-working assets in your operation. Extreme temperatures, rapidly fluctuating cycles of demand and exposure to humidity, salt, vibrations, corrosive elements and dirt can cause connections to loosen, creating a high resistance path that is responsible for more than 30% of electrical failures. If the wrong electrical asset goes down at the wrong time, it can bring your entire operation to a halt. For example, inspections often require equipment shutdown, which can be difficult to schedule for an operation that runs 24 hours a day. Manual inspection of equipment can also be dangerous for workers who are exposed to accidental electrocution. And because many manual inspections involve writing down data on a chart, this paper-based process makes it time- consuming to digitize data, while also introducing the risk of errors due to illegible handwriting or faulty manual data entry into a spreadsheet, resulting in decisions being made on incorrect data. Condition monitoring software, sensorization and IoT can help automate data collection by providing 24/7 continuous monitoring of equipment. Accurate digital data from every asset can be easily collected, stored, combined and analyzed without human intervention to give you a clear and complete understanding of your asset health, helping you accurately predict your maintenance requirements. Benefits include: • Achieve maintenance savings: Avoid unnecessary inspections and replacement of still-useful components, which can reduce time spent per asset, unplanned emergency maintenance and operating expenses. • Avoid unexpected downtime: Condition monitoring devices and sensors can track up to 70% of the most common failure causes, such as loose connections or joints, environmental conditions, faulty insulations and faulty mechanisms. — The benefits of predictive maintenance for electrical distribution assets • Improve safety: Remote condition monitoring allows field service staff to evaluate electrical systems from a safe distance, helping avoid incidents that can cause injury or loss of production and equipment. • Extend the life of assets: Most electrical equipment has a failure rate curve shaped like a bathtub, with the probability for failure increasing as it nears its average end of life. Condition monitoring and predictive analytics help detect possible wear out and abnormal conditions in advance so that mitigation can occur before a failure occurs, prolonging the asset's life. Failure rate statistics of Industrial MV and LV electrical distribution. Source: based on ABB experience. — Source: based on ABB experience on industrial MV and LV electrical distribution Manual (corrective or time based) Automatic (condition monitoring) Temperature power parts inpection (requires shutdown) Continuous joints temperature monitoring (detect loose connections) Environment assessment (might require shutdown) Continuous environmental monitoring (temperature, humidity, etc) Insulation inspection and tests (might require shutdown) Continuous partial discharge monitoring (detect insulation degradation) Circuit Breaker Periodical tests (requires shutdown) Continuous electro-mechanical operations monitoring with protection relays 7% Loose connections / joints Environment & humidity Incorrect work 3% 9% 10% 34% 17% 20% Faulty insulation / short circuit Faulty equipment (mechanical) Other Overload m A K I N G p r e D I C T I v e m A I N T e N A N C e pAy 11 Of course, digitalization of existing equipment, like adding sensors and condition monitoring software, can come with its own costs. The correct selection of digital upgrading kits for legacy systems is key to making predictive-based maintenance sustainable. — Making predictive maintenance pay That’s why it’s important to have a clear ROI target to determine if the costs are worth the benefits for your specific use cases and operation. It is here where a manufacturer’s expertise, combined with your maintenance engineers’ internal knowledge, can help you best determine your strategic approach to maintenance. For example, a clean and dry environment might not require environmental monitoring, but may require continuous thermal monitoring of the main joints using thermal cameras on live equipment to avoid expensive inspection. However, assets in another part of your operation may require partial discharge to monitor insulator reliability, as well as thermal and environmental monitoring. Rather than one-size-fits-all, you should seek to find an approach that is “one-size-fits-you.” -16.000 -8.000 0 8.000 16.000 24.000 32.000 Failure avoidance savings Commissioning Predictive analytics subscription (OPEX) Predictive maintenance savings (vs time-based maintenance) Initial condition monitoring and sensors commissioning (CAPEX) ROI Example of predictive maintenance return on investment (1.6 years) for a medium voltage switchgear 1y 2y 3y 4y 5y 12r e T h I N K I N G A S S e T p e r f o r m A N C e m A N A G e m e N T f o r T h e D I G I TA l A G e AT U T I l I T I e S — The benefits of predictive maintenance for electrification distribution assets In the past, conventional asset management solutions have faced a series of challenges: • Large upfront investments, especially when digitizing existing assets • Slow, complicated implementation processes • Time-consuming training due to solution complexity • Difficulty implementing and customizing predictive models • A “run-to-failure” maintenance culture unused to the work process of predictive maintenance These challenges can jeopardize or postpone the ROI of predictive maintenance, or even create a barrier to implementation. But with an Asset Performance Management as a Service (APMaaS) solution augmented by digital technologies such as sensorization, cloud connectivity and advanced analytics, you can immediately achieve valuable returns through reduced inspections, fewer emergency services and asset performance traceability. Benefits of an APMaaS solution include: • Simplicity: APMaaS solutions enable a pure IoT architecture that makes it simple to collect data from new and existing equipment, helping you eliminate time-consuming and error-prone manual data collection, or a complex and expensive revamping. • Flexibility: These solutions can be implemented anywhere there is an internet connection, allowing asset managers to stay connected to their real-time asset performance no matter where they are. • Scalability: Solutions can be implemented on a small-scale to cover your most pressing needs or greatest opportunities, and then scaled throughout the facility when additional features or coverage is required. For instance, maintenance management, energy management, and other powerful functions can be easily enabled and used. • Ease of implementation: Edge/cloud solutions don’t require a server computer to install or run applications, making it simple to add new sensors as needed. • Cost savings: Cloud-based solutions are charged as a subscription service, helping you avoid large upfront investments while ensuring you pay only for the solutions you actually use. Asset performance management is easy to implement at just one site or across a multi-site environment. Your software will create a digital twin of physical assets that allow you to remotely dive into the details, while powerful analytics will provide easy-to-understand asset health information and actionable recommendations for recommended maintenance – no complex tools, software, or mathematical calculations required. In addition, the solution will provide a single source of truth for your assets, giving your entire staff equal access to asset conditions from the highest level down to the most minute detail. Solutions can come in many different sizes, shapes and features and depending the requirements they may take on different forms. T h e B e N e f I T S o f p r e D I C T I v e m A I N T e N A N C e f o r e l e C T r I f I C AT I o N D I S T r I B U T I o N A S S e T S 13 Three possible solutions are: 1. Onsite or On-premise: This solution provides a central computer within the internal network of a facility. The computer hosts the software that will connect to devices to monitor, analyze, and alert. This is usually a custom engineered solution providing key information on assets as per the end users requirements. Custom algorithms can be created to further monitor and analyze each asset and provide a prediction of when an asset might need maintenance or even when it might fail. Access to this solution is usually via a workstation within the facilities network only. 2. Hybrid: This solution using a combination of an onsite computer along with a cloud solution to provide vital information for each asset. This solution is partially a custom engineered solution and uses pre-defined information on assets along with additional features when connected to the cloud. Features include load forecasting, energy forecasting, asset trending over large period of times, years vs. months of data shortage compared to a fully onsite solution. Access to this solution can be either by local workstation or by secure internet connection to the cloud. 3. Cloud: This solution provides the same as the onsite and hybrid solutions plus more access to vital statistics and analysis on critical assets anywhere there is an internet connection. Algorithms for predictive features like Predictive Maintenance are constantly learning, growing, and adjusting based on real time date from each asset. Increased access to features like load forecasting, energy usage, trends, costs, asset status, alerts, alarms, and reports. 14 R E T H I N K I N G A S S E T P E R F O R M A N C E M A N A G E M E N T F O R T H E D I G I TA L A G E AT U T I L I T I E S ABB customer success story ABB’s asset management solutions can help provide the insights you need to prevent critical asset failures while maximizing asset lifecycle costs for greenfield and brownfield applications. Learn more about ABB Asset Performance Management. — Optimize your asset management with ABB As the most proven and efficient asset performance management solution available on the market, its speed of implementation and extensibility allow you to start lean, experiment and learn, and accelerate your organization’s digital transition while savings are materialized. A smart grid, for a utility, is not just efficient power flow monitoring, control and protection, but also an accurate and continuous evaluation of the assets condition to avoid unwanted power interruptions and expensive emergency and restoration services. Customer therefore adopted during a modernization journey ABB Ability™ solutions for asset management for their distribution substations, bringing truly digitalization at the grid. — ABB Inc. 305 Gregson Drive Cary, NC 27511 United States electrification.us.abb.com/industries/utility electrification.us.abb.com/products/measuring-monitoring/abb-ability-energy- asset-manager 9AKK108467A4036 — We reserve all rights in this document and in the subject matter and illustrations contained therein. Any reproduction or utilization of its contents – in whole or in part – is forbidden without prior written consent of ABB Inc. © 2023 ABB Inc. All rights reserved. We reserve the right to make technical changes or modify the contents of this document without prior notice. With regard to purchase orders and/or contracts, the agreed particulars shall prevail. ABB Inc. does not accept any responsibility whatsoever for potential errors or possible lack of information in this document.