Based on this strategy, other governments and global industry leaders have gradually embraced the strategy worldwide as something fundamental to their future direction.
Based on this concept, in 2014 the German government declared Industry 4.0 to be a key part of their “High-Tech Strategy 2020 for Germany” initiative. The term Industry 4.0, known as the Fourth Industrial Revolution, was first introduced at the World Industrial Technology Fair in Hanover in 2011. The concepts of intelligent industry following Industry 4.0 standards allow us to fully virtualize and digitize industrial production processes for optimization purposes. We have many options nowadays for the optimization of existing or future logistics production processes in order to increase their competitiveness. To demonstrate the versatility of deployment, we chose a configuration simulating a robotic assembly workplace and its logistics. Optimization costs are also significantly reduced, as it is not necessary to verify the optimization impact directly in production, but only in the physical model. The model fully physically reproduces the real conditions of simulated production and verifies in advance the quality of proposed optimization changes virtually by the digital twin.
Therefore, we created a universal CPS based on requirements from our cooperating manufacturing companies. Such concerns are justified because the proposed changes in the optimization of production logistics based on simulations from a digital twin tend to be initially costly and affect the existing functional production infrastructure. The possibility of an initial test of the physical implementation of proposed optimization changes before they are fully implemented into operation is a pragmatic question that still resonates on the production side. Virtualization techniques in the form of a digital twin are standardly used for this purpose. Especially in fully functional production facilities, there is a trend towards optimizing logistics systems in order to increase efficiency and reduce idle time. Since the digital twin requires a physical connection to a real line for its operation, this connection is substituted by a modular cyber-physical system (CPS), which replicates the same physical inputs and outputs as a real production line. The basic idea is the direct possibility of testing and debugging advanced logistics algorithms using a digital twin outside the production line.
This paper deals with the design and implementation of a universal cyber-physical model capable of simulating any production process in order to optimize its logistics systems.
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