Selection of data mining method for multidimensional evaluation of the manufacturing process state

The article deals with the issues involved in evaluating the process state on the basis of many measures, including: process parameters, diagnostic signals and events occurring during the process. These measures as well as those measurements traditionally used in the evaluation of process capability, offer a relevant source of information about the manufacturing process and the authors attempted to ascertain the most suitable method, or group of methods, for achieving this. They present the main criteria for the categorization division of the methods of the manufacturing process state evaluation and, from those identified, distinguish the traditional from Data Mining methods. The authors then specify some basic requirements regarding the desired method or group of methods and focus on the classification problem. A division and classification of the methods is made and briefly described. Finally, the authors specify the criteria for their selection of the Data Mining method type as being the most appropriate for the evaluation of the manufacturing process state and, from within this type, offer the most suitable groups of methods. Some directions for further research are discussed at the end of the article.