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Data-based quality analysis in machining production: Influence of data pre-processing on the results of machine learning models

机译:加工生产中基于数据的质量分析:数据预处理对机器学习模型结果的影响

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Quality assurance as a non-value-adding process is constantly reviewed for cost optimisation and potential savings. In the pursuit of utilising advanced data analysis and machine learning methods to improve efficiency of quality assurance in machining processes there are several influencing factors severely impacting the performance and hence the value of said methods. Especially data preparation is a time consuming task requiring both domain and data expert knowledge and yielding various options for data preparation. In this paper, the impact of different input data sets for predicting part quality in a drilling process is investigated, using machine control data.
机译:质量保证作为非价值添加过程,不断审查成本优化和潜在的节省。 在追求利用先进的数据分析和机器学习方法来提高加工过程中质量保证效率,有几种影响因素严重影响性能,从而影响了所述方法的价值。 特别是数据准备是一种耗时的任务,需要域和数据专家知识,并产生各种用于数据准备的选项。 本文采用机器控制数据研究了用于预测钻井过程中的部分质量的不同输入数据集的影响。

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