A fuzzy approach for the selection of non-traditional sheet metal cutting processes

Abstract

This work presents a methodology for the selection and comparison of non-traditional sheet metal cutting processes as a new structure of selection by means of an expert system. The model is generated from a knowledge base acquired from diverse experts, and the use of fuzzy logic techniques. With a simple input of the parameters of a piece, the system offers the most appropriate cutting options (based on the requirements of the piece) allowing a non-expert user selecting the most appropriate process with emphasis on a predefined priority: finish, cost or time. The selection process consists of four base algorithms that measure the attributes of each process as a dependent indicator of the other processes, that is, a pre-selection that considers (1) the process capability to cut a material-thickness relation, (2) the speed that can be achieved with this relation, (3) the inherent complexity of the piece to be cut, and (4) the process tolerance. Results of experiments under three different approaches prove that the expert system here presented accurately prioritizes the most convenient cutting processes.