Tool selection and cutting conditions optimization in milling

Autorea: Rafael Enparantza Agirre Tesi zuzendaria G. Barrow, University of Manchester Institute of Science and Technology Data1991

This thesis describes the features of an automatic tool selection module for rough and finish milling. The module is integrated in a manufacturing system for milling operations under development at UMIST. The procedure is algorithmic and can cater for the main types of milling cutters. The tool selection module looks for the optimum tool based on economic grounds so that it tries to select the tool or set of tools that would remove a given workpiece feature at minimum value fo the objective function, which is either the operation cost or the operation time. Therefore, its completion required an analysis of the optimization of cutting conditions which led to the enhancement of an existing package. New constraints were introduced and the optimum point search procedure accelerated. The result of selecting a set of tools to remove a given workpiece feature involved an operation planning arrangement at feature level.

The input to the module are basic elements of the cutting process, namely, the machine being utilized, the workpiece features to be produced from the blank and the available tools. The development of a data base to code and classify the various parameters was also iniciated.

Finally, several examples are presented to illustrate the capabilities of the programme. In view of the results, the limitations of rule based selection procedures as compared to the algorithmic approach implemented become apparent. The advantage of the latter is that it takes into consideration the entire cutting process with its three basic elements and, as a consequence, is able to identify the constraints operating in each case, which, as shown, directly influence tool economic performance.

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