This IDC TechBrief discusses the value for the electric utility industry of adopting digital twin technology and moving beyond traditional manual and discrete operational processes. A digital twin is an IT-powered platform where utility companies can build an exact replica of their physical assets in the cloud from design and development to the end of the product or asset life cycle. The digital twin will enable companies to gain efficiency in terms of manpower optimization, improved operations, reduced accidents, and faster time to market. A key feature of digital twins that will add significant value to electricity production and transmission operations are as follows: predictive analytics, machine learning/AI for self-learning analytical modeling, conversion of entire data sets to insight, continuous analysis of incoming data, 3D simulation platform for design optimization, and low-cost engineering planning.
Implementing a digital twin for the entire asset from scratch will be complicated and may raise concern among industry players. It requires lots of operational changes in the existing setup, deployment of IoT sensors across physical assets, and a separate, sizeable budget allocation. On top of that, CIOs or digital officers would be slightly skeptical about the duration and amount of payback of the required investment. Service providers/IT vendors will have to identify the most significant part to kick off the digital twin project.
"In the age of digitalization and growing penetration of digital solutions such as robotics, AI, AR/VR, and Big Data, a digital twin appears to be the only integration platform that can unite several existing or new technologies to be added to the dynamic business process. Therefore, it has potential to emerge as a solution to provide a holistic, immersive understanding and integrated comprehensive view of assets to industry leaders," said Gaurav Verma, research manager, IDC Energy Insights EMEA.
IDC Energy Insights: Europe, Middle East and Africa Utilities Digital Transformation Strategies
Analytic applications, Augmented and virtual reality, Cognitive/artificial intelligence, Digital transformation, Engineering applications, Enterprise asset management, Internet of things, Technology buyer