Genetic Algorithm Applied to Investigate Cutting Process Parameters Influence on Workpiece Price Formation

Abstract

In this work, genetic algorithm (GA) technique was applied to investigate cutting process parameters influence on workpiece price formation using the concepts of contribution margin. The cutting process is one of the most important processes among many others available in manufacturing scenarios. Nevertheless, it is common to find some manufactured item, or at least one part of it, that was made, by cutting process. Because of its importance, many studies related to its optimization were performed, and in the last years, cutting process optimization task has been explored in different approaches from several knowledge areas, such as deterministic methods, operational research and artificial intelligence, and design of experiments. The obtained results from GA application presented in this work are in good agreement with others already reported and could be properly used in cutting process optimization parameters.

Keywords:

• Artificial intelligence
• Contribution margin
• Cutting process
• Genetic algorithm
• Parameters optimization