Physics-based simulation framework for Digital Twin applications: Machine parameter tuning for handling of lumber in the wood industry

Abstract

Tuning the operational parameters of complex handling machines involves a complex interplay of variables impacting the performance and reliability of the equipment and the processes being executed. By integrating advanced simulation tools in DTs architectures, manufacturers can predict and analyse the performance of machines under various settings and scenarios. This paper proposes a physics-based simulation framework designed for offline optimisation of machine parameters and for integration in Digital Twin applications to explore the configuration space of machine parameters for their selection and fine-tuning. The framework enables virtual exploration of the parameter space to identify optimal parameter settings in terms of productivity and stability for both design-phase analysis and machine setup optimisation. While developed as a simulation component suitable for integration within Digital Twin architectures, the current implementation operates independently of real-time data integration. A case study from the wood industry demonstrates the application and validation of the approach under realistic operational scenarios, showing the framework’s potential for deployment in Digital Twin systems.