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Automated statistical evaluation of energy data in the automotive production

机译:汽车生产中能源数据的自动统计评估

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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.
机译:在制造业中,强烈需要评估与能源相关的数据(如能源负荷曲线)的方法。所获得的能量数据可用于商业生产系统规划和仿真软件解决方案。但是,由于缺少自动评估解决方案,因此缺少例如机床或公用事业。因此,业界试图弥合软件与实测能源数据之间的差距。本文的目的是为生产设备开发一种自动的能量负荷曲线分析,以提供消耗数据以供进一步使用,例如:在工厂的早期规划阶段。所提出的方法的主要优点是仅减少能量数据上的输入数据以识别例如燃料。机器状态取决于能源需求。为此,应用了统计方法和聚类算法。该方法以汽车行业的用例为例。

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