文章基本信息

标题：A Comparison Between Data Mining Prediction Algorithms for Fault Detection-Case study Ahanpishegan Co.
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作者：Golriz Amooee ; Behrouz Minaei-Bidgoli ; Malihe Bagheri-Dehnavi 等
期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2011
卷号：8
期号：6
出版社：IJCSI Press
摘要：In the current competitive world, industrial companies seek to manufacture products of higher quality which can be achieved by increasing reliability, maintainability and thus the availability of products. On the other hand, improvement in products lifecycle is necessary for achieving high reliability. Typically, maintenance activities are aimed to reduce failures of industrial machinery and minimize the consequences of such failures. So the industrial companies try to improve their efficiency by using different fault detection techniques. One strategy is to process and analyze previous generated data to predict future failures. The purpose of this paper is to detect wasted parts using different data mining algorithms and compare the accuracy of these algorithms. A combination of thermal and physical characteristics has been used and the algorithms were implemented on Ahanpishegans current data to estimate the availability of its produced parts.
关键词：Data Mining; Fault Detection; Availability; Prediction Algorithms.