Continuous Validation and Updating for High Accuracy of Digital Twins of Production Systems

Despite continuous improvements in modelling, software tools and data availability, simulation projects of production systems still require a lot of manual effort, expertise in various disciplines and time. In many projects the high initial invest for building the simulation model is followed by a rather short period of experimentation and analysis. As production systems have to be adapted at an increasing pace to respond to rapidly changing markets and business environments, simulation models of these systems become outdated earlier, reducing their useful time window. One way to extend this time window would be the implementation of a method of automated comparison with the current production systems and subsequent self-adaption of the model to reality to maintain and even improve its accuracy over time. This approach will be presented and validated at a real world use case. Such an enhanced simulation model can be called a digital twin of the production system.