This blog series discusses the complex tasks energy utility companies face as they shift to holistic grid asset management to manage through the energy transition. Earlier posts in this series addressed the challenges of the energy transition with holistic grid asset management, the integrated asset management platform and data exchange, and merging traditional top-down and bottom-up planning processes.
Asset management and technological innovation
Advancements in technology underpin the need for holistic grid asset management, making the assets in the grid smarter and equipping the workforce with smart tools.
Robots and drones perform inspections by using AI-based visual recognition techniques. Asset performance management (APM) processes, such as risk-based and predictive maintenance and asset investment planning (AIP), enable health monitoring technologies.
Technicians connect to the internet by wearable devices such as tablets, watches or VR glasses, providing customers with fast access to relevant information or expert support from any place in the world. Technicians can resolve technical issues faster, improving asset usage and reducing asset downtime.
Mobile-connected technicians experience improved safety through measures such as access control, gas detection, warning messages or fall recognition, which reduces risk exposure and enhances operational risk management (ORM) during work execution. Cybersecurity reduces risk exposure for cyberattacks on digitally connected assets.
Sensoring and monitoring also contribute to the direct measurement of sustainability environmental, social and governance (ESG) metrics such as energy efficiency and greenhouse gas emission or wastewater flows. This approach provides actual real data points for ESG reporting instead of model-based assumptions, which helps reduce carbon footprint and achieve sustainability goals.
The asset management maturity journey
Utility companies can view the evolution of asset management as a journey to a level of asset management excellence. The following figure shows the stages from a reactive to a proactive asset management culture, along with the various methods and approaches that companies might apply:
In the holistic asset management view, a scalable platform offers functionalities to build capabilities along the way. Each step in the journey demands adopting new processes and ways of working, which dedicated best practice tools and optimization models support.
The enterprise asset management (EAM) system fundamentally becomes a preventive maintenance program in the early stages of the maturity journey, from “Innocence” through to “Understanding”. This transition drives down the cost of unplanned repairs.
To proceed to the next level of “Competence”, APM capabilities take the lead. The focus of the asset management organization shifts toward uptime and business value by preventing failures. This also prevents expensive machine downtime, production deferment and potential safety or environmental risks. Machine connectivity through Internet of Things (IoT) data exchange enables condition-based maintenance and health monitoring. Risk-based asset strategies align maintenance efforts to balance costs and risks.
Predictive maintenance applies machine learning models to predict imminent failures early in the potential failure curve, with sufficient warning time to allow for planned intervention. The final step at this stage is the optimization of the maintenance and replacement program based on asset criticality and available resources.
APM and AIP combine in the “Excellence” stage, and predictive generative AI creates intelligent processes. At this stage, the asset management process becomes self-learning and prescriptive in making the best decision for overall business value.
New technology catalyzes the asset maturity journey, digital solutions connect the asset management systems, and smart connected tools improve quality of work and productivity. The introduction of (generative) AI models in the asset management domain has brought a full toolbox of new optimization tools. Gen AI use cases have been developed in each step of the journey, to support companies develop more capabilities to become more efficient, safe, reliable and sustainable. As the maturity of the assets and asset managers grows, current and future grid assets generate more value.
Holistic asset management aligns with business goals, integrates operational domains of previously siloed disciplines, deploys digital innovative technology and enables excellence in asset management maturity. This approach allows utility companies to maximize their value and thrive as they manage through the energy transition.
Source: ibm.com
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