Automated statistical evaluation of energy data in the automotive production

In the manufacturing industry, there is a strong demand for methods evaluating energy related data like energy load profiles. The obtained energy data can be used in commercial production system planning and simulation software solutions. However, due to missing automated evaluation solutions, there is a lack of data for e.g. machine tools or utilities. Therefore, the industry tries to bridge the gap between software and measured energy data. The aim of this article is to develop an automated energy load profile analysis for production equipment to provide consumption data for further uses, e.g. in the early factory planning phase. The main advantage of the presented method is the reduction of input data only on energy data to identify e.g. the machine state depended energy demand. To achieve this, statistical methods and clustering algorithms are applied. The approach is exemplified by a use case from the automotive industry.