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Application of time series data mining for the prediction of transition times in production

机译:时间序列数据挖掘在生产中转换时间预测中的应用

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Transition times between value-adding operations often account for more than 90 % of lead times in workshop productions and vary greatly from order to order. However in day-to-day business, they are treated as static master data or only roughly estimated. One approach for a more precise prediction of future transition times of production orders is time series data mining. This paper presents a first application approach as basis for improving the quality of production planning. Based on empirical findings, future research issues are derived.
机译:价值添加操作之间的过渡时间经常占工作坊生产中的90%以上的交货时间,并且从订单下差异很大。但是,在日常业务中,它们被视为静态主数据或仅粗略估计。一种更精确地预测生产订单的未来转换时间的一种方法是时间序列数据挖掘。本文提出了提高生产规划质量的第一种应用方法。基于实证调查结果,得出了未来的研究问题。

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