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Title: A Vision and Robot Based On-line Monitoring of Defects in Electronics Manufacturing: A Collaborative Effort in Capstone Project PDF
Url: http://search.asee.org/search/fetch?url=file%3A%2F%2Flocalhost%2FE%3A...
Creator: Bose, Subhash
Edinbarough, Immanuel
Publisher: University of Texas at Brownsville
Description: 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 Matlabs 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.
LC Classification: Education -- Theory and practice of education -- Teaching (Principles and practice) -- Instructional systems -- Instructional systems design
Technology -- Electrical engineering. Electronics. Nuclear engineering -- Electrical engineering. Electronics. Nuclear engineering -- General electrical manufacturing and engineering companies
Technology -- Mechanical engineering and machinery -- Mechanical devices and figures. Automata. Ingenious mechanisms. Robots (General) -- Personal robotics
GEM Subject: Science -- Engineering
Science -- Instructional issues
Vocational Education -- Trade and industrial
Date Issued: 2004
Resource Type: Reading Materials
Reference
Science Materials
Teaching Guides
Format: pdf
Audience: College/University Instructors
Higher Education
Students
Teachers
Technical School First Cycle
Technical School Second Cycle
University First Cycle
University Second Cycle
Vocational Training
Language: English
Rights: American Society for Engineering Education
Access Rights: Free access
Date Of Record Release: 2009-07-22 03:00:02 (W3C-DTF)
Date Last Modified: 2012-05-31 13:51:25 (W3C-DTF)
Source Type: ATE Center
Source: National Center for Manufacturing Education
Full Record Views: 89
Resource URL Clicks: 19
Cumulative Rating: NOT YET RATED
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