... applications. In this context, the literature presents systematic procedure models to generate knowledge from data, such as the cross industry standard process for data mining (CRISP-DM) model, which is used as a standard methodology for conducting data mining in industrial applications. However, these models...

... , pp. 3 – 12 . [30] Fayyad , U. M. , Piatetsky-Shapiro , G. , and Smyth , P. , 1996 , “ From Data Mining to Knowledge Discovery in Databases ,” AI Mag. , 17 ( 3 ), pp. 37 – 54 . 10.1609/aimag.v17i3.1230 [31] Gabriel , R. , Gluchowski , P. , and Pastwa , A. , 2009...

...J. A. Harding; M. Shahbaz; Srinivas; A. Kusiak The paper reviews applications of data mining in manufacturing engineering, in particular production processes, operations, fault detection, maintenance, decision support, and product quality improvement. Customer relationship management, information...

...Bruno Agard, Assistant Professor,; Andrew Kusiak, Professor, The paper presents a model and an algorithm for selection of subassemblies based on the analysis of prior orders received from the customers. The parameters of this model are generated using association rules extracted by a data mining...

...Andrew Kusiak, Professor Data mining offers methodologies and tools for data analysis, discovery of new knowledge, and autonomous process control. This paper introduces basic data mining algorithms. An approach based on rough set theory is used to derive associations among control parameters...