As the use cases for digital twins proliferate, it is becoming clear that data-driven enterprises with a track record of innovation stand the best chance of success. Credit: AWS | IBM Changing complex business processes or trying to innovate amid a sophisticated ecosystem poses risks of disruption and escalating costs. This explains why IT leaders with a remit to transform their businesses are increasingly turning to digital twin technology to effectively simulate big changes before they go live. IBM defines a digital twin as a virtual model that accurately reflects a physical object (or a system). The “twin” consists of data, generated by sensors fitted to the original physical object or system, which track performance such as energy output, temperature and weather conditions. The logic of digital twin technology can be applied to challenges as diverse as supply chains, retail merchandising, customer churn propensity, risk modelling, fraud detection, cybercrime, fluid dynamics and personalised gene therapy. In sectors like energy and manufacturing, digital twins is already helping to design better products with improved resource management, which will benefit the environment. Updated with real-time data, digital twins will also allow companies to assess and predict the performance of components and complex […]
How digital twin technology is changing complex industrial processes forever
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