A Teaching System Fostering Expertise for the Tuning of Printed Circuit Board Inspection Systems

Japanese manufacturing companies are now facing a real shortage of skilled workers who have expertise on production facilities and instruments. Automating their tasks by machine may be one promising solution to this problem. However, it is not enough. The future production facilities should be designed so that it can develop and nurture workers' qualities and skills to overcome the "deskilling" problem caused by automation. This paper deals with the printed circuit board inspection system utilized in manufacturing sites, and we develop an automated teaching system for tuning the parameters of the inspection system so that it can work being customized to particular site conditions. This tuning task has been left to the expertise of the skilled system engineers. However, our developing teaching system enables non-expert users to achieve accurate tuning equivalent to an expert's level. We show that our teaching system can improve the accuracy of the tuning task drastically. Moreover, we present our system can encourage non-experts to enhance their skills for the tuning, which is verified by investigating into the verbal expressions on their expertise that is analyzed by usage of the fuzzy structural modelling technique. The result shows that a non-expert user's knowledge cultivated by usage of our teaching system can change to the one similar to what an expert has.