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In-Line Identification of Two-Dimensional Surface Profile and Defects Using a High-Precision Automated Optical Inspection System With a Cloud-Aided Statistical Analysis System

[+] Author Affiliations
Boting Rex Lin, Wei-Hao Lu, Po Ting Lin, Ming Chang, Mark Christian E. Manuel

Chung Yuan Christian University, Chungli, Taoyuan, Taiwan

Paper No. DETC2015-46132, pp. V009T07A048; 8 pages
  • ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 9: 2015 ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications
  • Boston, Massachusetts, USA, August 2–5, 2015
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5719-9
  • Copyright © 2015 by ASME


Automated Optical Inspection (AOI) systems are expected to replace manual inspection especially for flat and flexible electronic component systems, which require high yield and high speed. A high precision AOI system calibrated for 3.5 microns per pixel resolution was previously developed for defect detection of flat glass where imperfections and defects are obtained with minimal image processing techniques. Due to the large image size, cloud based image processing cannot be performed at the moment but cloud based statistical tools and visualization are now becoming more popular. This paper extends the previous work by adding two-dimensional surface profiling and defect detection for a flexible PCB, more specifically, a digitizer for mobile devices. A non-referential inspection method was sought with the widths of deposited metal wires on the digitizer substrate measured using distance transform. The wire width information is then sent to a web server and statistically processed. Display outputs in the form of Shewhart Xbar and S process control charts are then used as basis to quantify the line information and possibly investigate possible surface defects.

Copyright © 2015 by ASME



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