Industrial utilization of linguistic equations for defect detection on printed circuit boards

This paper describes how linguistic equations, an intelligent method derived from fuzzy algorithms, have been used in a decision-helping tool for electronic manufacturing. In our case the company involved in the project, PKC Group, is mainly producing control cards for the automotive industry. In their business, nearly 70 percent of the cost of a product is material cost. Detecting defects and repairing the printed circuit boards is therefore a necessity. With an ever increasing complexity of the products, defects are very likely to occur, no matter how much attention is put into their prevention. That´s the reason why the system described in this paper comes into use only during the final testing of the product and is purely oriented towards the detection and localization of defects. Final control is based on functional testing. Using linguistic equations and expert knowledge, the system is able to analyze that data and successfully detect and trace a defect into a small area of the printed circuit board. If sufficient amount of data is provided, self-tuning and self-learning methods can be used. Diagnosis effectiveness can therefore be improved from detection of a functional area towards component level analysis.