Application of a Simulation-Based Digital Twin for Predicting Distributed Manufacturing Control System Performance

During the last years, several research activities and studies have presented the possibility to perform manufacturing control using distributed approaches. Although these new approaches aim to deliver more flexibility and adaptability to the shop floor, they are not being readily adopted and utilised by the manufacturers. One of the main challenges is the unpredictability of the proposed solutions and the uncertainty associated with these approaches. Hence, the proposed research aims to explore the utilisation of Digital Twins (DTs) to predict and understand the execution of these systems in runtime. The Fourth Industrial Revolution is leading to the emergence of new concepts amongst which DT stand out. Given their early stage, however, the already existing implementations are far from standardised, meaning that each practical case has to be analysed on its own and solutions are often created from scratch. Taking the aforementioned into account, the authors suggest an architecture that enables the integration between a previously designed and developed agent-based distributed control system and its DT, whose implementation is also provided in detail. Furthermore, the digital model's calibration is described jointly with the careful validation process carried out. Thanks to the latter, several conclusions and guidelines for future implementations were possible to derive as well.

Automated summary

Research explores the use of Digital Twins to predict and understand the execution of distributed manufacturing control systems. However, due to the early stage of Digital Twins technology, existing implementations are far from standardized, requiring analysis and solution development based on individual cases.