Abstract
AbstractEnergy efficiency is becoming increasingly important for industry. Many approaches for energy efficiency improvements lead to the purchase of new hardware, which could neglect the sustainability. Therefore, optimizing the energy demand of existing machine tools (MT) is a promising approach. Nowadays energy demand optimization of MT in series production is mainly done manually by the operators, based on implicit knowledge gained by experience. This involves manual checks to ensure that production targets like product quality or cycle time are met. With data analytics it is possible to check these production targets autonomously, which allows optimizing production systems data driven. This paper presents the approach and evaluation of a closed loop energy demand optimization of auxiliary units for milling MT during series production. The approach includes, inter alia, a concept for machine connectivity using edge devices and a concept for validating production targets.
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