Cluster analysis, unlike most mathematical and statistical methods, does not impose any restrictions on the type of objects under consideration, and allows us to consider a lot of input data of almost arbitrary nature. Cluster analysis allows you to consider a fairly large amount of information and dramatically reduce, compress large amounts of technological information, make them compact and intuitive. The attributes of the “equipment” cluster are entered into the matrix, the rows of which also correspond to the elements of the technology content, and the columns contain the attributes of the equipment. The matrix is also filled with the necessary characteristics of objects that are not included in the list of cluster features. The entire set of calculated quantities was combined in accordance with their functional purpose in groups. Based on the analysis, the relationships and dependencies between the clusters can be established by the same signs and parameters by which the clusters were previously formed. There are a lot of different relationships and dependencies between clusters of equipment, tools and work pieces.
Volume 11 | 12-Special Issue
Pages: 1371-1375
DOI: 10.5373/JARDCS/V11SP12/20193356