数据挖掘方法在制造业中的应用

Eva Tylečková, Darja Noskievičová
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引用次数: 0

摘要

本文介绍了数据挖掘作为一种分析工业过程数据的合适工具。数据挖掘方法在当今数字化、大数据处理和分析的时代提供了广泛的用途。除了发现模式和检测个体特征之间的关系、确保产品质量、预测和优化过程性能之外,数据挖掘技术还有助于在解决问题时从被动方法过渡到预测方法。论文的第一部分介绍了利用数据挖掘方法和技术分析工业过程数据的可能性。论文的第二部分讨论了数据挖掘方法的选择及其在制造业数据中的实际应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Utilization of Data Mining Methods in Manufacturing Industry
The paper presents data mining as a suitable tool for analyzing data from industrial processes. The data mining methods offer a wide range of uses in the current age of digitalization, big data processing and analysis. Apart from discovering patterns and detecting relationship between individual characteristics, assuring quality of products, prediction and optimization of process performance, data mining techniques also contribute to the transition from a reactive to a predictive approach in problem solving. The first part of the paper presents the possibilities of utilization of data mining methods and techniques to analyze data from industrial processes. The second part of the paper deals with a selection of proper data mining method and its practical application on data from manufacturing industry.
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