Cost Benefit Analysis for Digital Twin Model Selection at the Time of Investment.

Abstract

Our ability to twin the digital and physical worlds can now be achieved through a broad range of low-to-high fidelity sensors and simulation and modelling techniques including analytical, numerical and artificial intelligence. The challenge for Digital Twins is now moving from the technical exercise of achieving the Digital Twin to how we categorise Digital Twin architectures and how we can predict the cost benefit when investing. This paper explores some existing categorisations of the model component of the Digital Twin and examines the variance in cost-benefit of two Digital Twin model components for twinning the location of a thermally sensitive assembly.

Topics & Concepts