“Proceedings of the 2004 American Society for Engineering Education Annual Conference & Exposition Copyright ©2004, American Society for Engineering” Session 3447 A vision and robot based on-line monitoring of defects in Electronics Manufacturing – A collaborative effort in capstone project. Immanuel Edinbarough, Subhash Bose The University of Texas at Brownsville/The University of Texas – Pan American Abstract This paper discusses the integration of an automated neural network-based vision inspection system with robots to detect and report IC lead defects on-line. The vision system consists of custom software that contains a neural network database for each IC to be inspected on a PCB. The vision system uses gray scale images and a single layer neural network with three outputs based on defect criteria. Each IC has different inspection area, thus, the input vector varies for each ICs. The IC networks were trained with Matlab’s Bayesian regularization module. This module was used because it prevents over and under training the image data. Performance of each of the networks investigated was found to be 100% based on the defect criteria. An on-line robotic inspection monitoring system has been developed, using ProE, C++ and OpenGL software 1,2 . Technical issues and collaborative efforts in the execution of this capstone project are discussed in the paper. This research project was embarked as a collaborative effort between the senior design project students of the University of Texas at Brownsville and a graduate student of manufacturing engineering at the University of Pan American. I Introduction Capstone design courses provide excellent opportunity for students to work on the open ended problems that have direct bearing on the real life industry situations. There have been several models reported in literature including the one that deal with students work in teams on industry sponsored projects and deliver a tested prototype at the end of the course to get credit. In this capstone project model, student teams are formed between a graduate student team and under graduate team. The student teams are from different colleges. There are advisors for each of the student teams from either of the institutions. The problem that was identified for the capstone project is a Page 9.125.1