Conceptual design of fixtures using genetic algorithms

Fixture design is a complex and intuitive process, which demands rich experience from the designer. Multiple acceptable designs are possible for a given workpiece and hence the solution space is large. Recent advances in CAD/CAM, especially in artificial intelligence, have alleviated this problem by intelligently restricting the search space considered, thus opening the possibility of obtaining better designs. Researchers have used various techniques under the general rubric of artificial intelligence to solve the fixture design problem. The most common of these have been case-based reasoning and expert systems. However; these two common methods do not ensure that the resulting solution is efficient or optimal. In this paper we propose to combine complementarily the strengths of genetic algorithms and neural networks to develop a fixture design system. Results obtained using this combined multi-agent approach for the design of fixtures are promising.