Application of sustainability-oriented cyber physical production systems to grinding processes

Abstract

The sustainable operation of grinding processes depends on various parameters. Not only does the grinding process have an enormous influence on the quality produced and the use of resources, but the peripheral systems have to be considered as well. When networked into a complete system, a collection of parameters, state variables, performance criteria and external factors is created. However, without the appropriate framework and the targeted definition of these values, no directly producible reference to a sustainability-oriented operation of the grinding system can be established. To detect the correlations and dependencies of the variables, Industry 4.0 approaches can be used to digitalize the manufacturing system. Cyber physical production systems (CPPS), when specifically designed for sustainable operation of the manufacturing system, contribute a positive impact in terms of e.g. energy and resource efficiency. In principle, CPPS initially carry an environmental backpack due to the sensor technology and hardware to be integrated, which is balanced out over the application period of the CPPS and finally results in a positive impact. Nevertheless, it has already been shown that CPPS can be made predictable in their efficiency increase through their systematic development. These advantages of a systematic development can greatly simplify the use of CPPS, especially in grinding. The inaccuracies and non-determinable factors of a grinding process are minimized in this paper using the CPPS and a systematic methodical approach. Similarly, the targeted use of sensor technology achieves the maximum benefit in terms of quality and sustainable operation. The use case in this paper is related to a grinding system in which sensory components are integrated and thus a sustainability-oriented measurement and control concept is built up. Through the integration, clear potentials are recognizable, which can be related not only to the parameters and the product quality but also to the resource consumption.