Digital Twin of Injection Molding (DIM)

Process innovations alone—such as new communication and networking capabilities for machines in the plastics processing industry—led, for example, to a 2.3% reduction in costs in 2018 compared to the previous year. Communication interfaces such as OPC UA enable, among other things, the high-resolution recording of machine and process parameters. This data can be used for improved quality monitoring, which can contribute to further cost reductions.

Control concepts currently implemented in injection molding machines regulate only machine and process parameters that correlate with part properties. True control of part properties requires, on the one hand, inline measurement of the relevant quality parameters and, on the other hand, dynamic process models of the entire chain of effects. The dynamic models—i.e., the digital twin—can then be used for model-based control or regulation.

The goal of the DIM project is to generate competitive advantages for SMEs by enabling them to create digital twins of their production facilities and use them to optimize the production process. To achieve this goal, methods and algorithms will be developed for recording high-resolution process parameters, capturing quality metrics in real time, data-driven modeling of the digital twin, and optimizing the production process based on this twin. The knowledge generated during this method development will be made available to companies through needs-based knowledge and technology transfer in the form of workshops and guidelines, enabling them to independently develop such systems in the future.