The process industry is characterized by two value chains. These are the horizontal supply chain and the vertical asset life cycle, both of which converge in production. The efficiency of the overall system is significantly determined by the fast and comprehensive availability of reliable information from all parts of these two value chains. For example, a change in raw material quality may require changes in production that may already have been investigated and are available in process development. Digitalization will bring significant benefits in this respect and increase process reliability, efficiency and finally profitability.
The digital twin will play a central role in this process, mapping the processes in the supply chain and the asset life cycle (see Figure 1). The digital twin is a virtual representation of the physical objects, brings together data and knowledge from the asset life cycle and the supply chain and continuously updates these. The Digital Twin also includes models that simulate processes and conditions in the real world. The models are able to access all data from the supply chain and the asset life cycle and realize relationships that are currently not visible. Physically based and modern data-driven and hybrid models are employed.
In this form, the digital twin enables fast and comprehensive access to information from all areas. In addition, a wide range of opportunities arise from the model-based evaluation of the data, which results then flow back into the real world and have an influence on it. For example, the wear condition of a component can be predicted on the basis of design and operating data, or data-driven dynamic process models can support the dynamic optimization of process control.
Of course, a digital twin will not completely map the supply chain and the asset life cycle, but can be limited to partial areas. However, the decisive factor is automated continuous data synchronization with the real world, which requires standardized data models that are still under development. Such data models are already available in some areas. The development of suitable models that incorporate a wide variety of data has also only just begun and still requires more development efforts.
Figure 1: Schematic illustration of the digital twin as an image of the value chains of the real process world, i.e. the horizontal supply chain and the vertical asset life cycle (Source: Bröcker, Evonik)