Modelling for Digital Twins - Potential Role of Surrogate Models
The application of white box models in digital twins is often hindered by missing knowledge, uncertain information and computational difficulties. Our aim was to overview the difficulties and challenges regarding the modelling aspects of digital twin applications and to explore the fields where surrogate models can be utilised advantageously. In this sense, the paper discusses what types of surrogate models are suitable for different practical problems as well as introduces the appropriate techniques for building and using these models. A number of examples of digital twin applications from both continuous processes and discrete manufacturing are presented to underline the potentials of utilising surrogate models. The surrogate models and model-building methods are categorised according to the area of applications. The importance of keeping these models up to date through their whole model life cycle is also highlighted. An industrial case study is also presented to demonstrate the applicability of the concept.
Integration of real-time locating systems into digital twins
Cyber-physical model-based solutions should rely on digital twins in which simulations are integrated with real-time sensory and manufacturing data. This paper highlights the benefits of information fusion with real-time locating systems (RTLS) and demonstrates how position and acceleration data can be utilised for the simulation-based analysis of product-specific activity times. The proposed digital twin is continuously capable to predict the production status and provide information for monitoring of production performance thanks to the real time connections of the RTLS and adaptive simulation models. The presented industrial case study demonstrates how the resulted Simulation 4.0 concept supports the analysis of human resource effectiveness (HRE) in an assembly process.