ICADA - INTELLIGENT COMPUTER-AIDED DEFECT ANALYSIS FOR CASTINGS

An intelligent computer aided defect analysis (ICADA) system, based on artificial intelligence techniques, has been developed to identify de sign, process or material parameters which could be responsible for th e occurrence of defective castings in a manufacturing campaign. The da ta on defective castings for a particular time frame, which is an inpu t to the ICADA system, has been analysed. It was observed that a large proportion, i.e. 50-80% of all the defective castings produced in a f oundry, have two, three or four types of defects occurring above a thr eshold proportion, say 10%. Also, a large number of defect types are e ither not found at all or found in a very small proportion, with a thr eshold value below 2%. An important feature of the ICADA system is the recognition of this pattern in the analysis. Thirty casting defect ty pes and a large number of causes numbering between 50 and 70 for each, as identified in the AFS analysis of casting defects-the standard ref erence source for a casting process-constituted the foundation for bui lding the knowledge base. Scientific rationale underlying the formatio n of a defect during the casting process was identified and 38 metacau ses were coded. Process, material and design parameters which contribu te to the metacauses were systematically examined and 112 were identif ied as rootcauses. The interconnections between defects, metacauses an d rootcauses were represented as a three tier structured graph and the handling of uncertainty in the occurrence of events such as defects, metacauses and rootcauses was achieved by Bayesian analysis. The hill climbing search technique, associated with forward reasoning, was empl oyed to recognize one or several root causes.