Optimisation of process planning functions by genetic algorithms
Computers and Industrial Engineering - Special issue on computational intelligence for industrial engineering
Selection of cutting tools and conditions of machining operations using an expert system
Computers in Industry
Integration of CAD and a cutting tool selection system
Computers and Industrial Engineering
Soft Computing and Hybrid AI Approaches to Intelligent Manufacturing
IEA/AIE '98 Proceedings of the 11th International Conference on Industrial and Engineering Applications of Artificial In telligence and Expert Systems: Tasks and Methods in Applied Artificial Intelligence
Computers and Operations Research
Expert Systems with Applications: An International Journal
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Today an extensive variety of cutting tool is available to suit different cutting situations and needs. Cutting tool selection is a very important subtask involved in process planning activities. This paper proposes the application of the particle swarm optimization (PSO) process for the definition of the optimal cutting tool geometry. This optimization model was developed considering an approach to the macro-level optimization of tool geometry in machining model satisfying technological constraints. To determine the most appropriate configuration of the algorithm and its parameters a set of tests were carried out. The different parameters settings were tested against data obtained from the literature. A variety of simulations were carried out to validate the performance of the system and to show the usefulness of the applied approach. The definition of proposed system also has presented the following main conclusion: through the utilization of the PSO approach, the selection of the appropriate cutting tool geometry is possible in real world environments.