Abstract
The concept design of checking fixtures for auto-body parts is a highly complex process that requires a human designer to draw from his rich experience. By exploiting recent advances in CAD/CAM and artificial intelligence techniques, one may constrain multiple solutions such that only good designs are considered. In this paper, a method of selecting type for checking fixtures is proposed that harnesses advantages of neural networks. This method attempts to capture relevant domain knowledge and is used to produce acceptable solutions. The method is applied to a case problem and the suggested checking fixture type is compared to one offered by a human designer. The agreement between the two solutions is very close.
Published Version
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