Analysis and evaluation of grouping methods for effective cutting tool operation
This article presents the possibilities for using cluster analysis in the assignment of machine tools in automated manufacturing systems. Based on the similarity of manufacturing processes in the system, cutting tools have been grouped. The objective was to obtain groups of similar objects, which could potentially ensure the reduction of the frequency and time of setups, optimizing the maintenance of tool resources and improving the efficiency and quality of production. With the application of similarity coefficients and hierarchical clustering algorithms, tool sets were formed with their composition specified. The assumed key factor was the limited tool magazine capacity for the machine tool. Therefore, it was necessary to separate the group with the largest multiplicity, not exceeding the assumed tool magazine capacity, from each group. The final part of the study includes an evaluation of the obtained solutions with selected measures used.
Michał Dobrzyński, Włodzimierz Przybylski. (2018). Analysis and evaluation of grouping methods for effective cutting tool operation, (1(108)), 53-61.
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