Full Content is available to subscribers

Subscribe/Learn More  >

Optimal Camera Path Planning for the Inspection of Printed Circuit Boards Using a Two Stepped Optimization Approach

[+] Author Affiliations
Zainab Hermes, Ashraf O. Nassef, Lotfi K. Gaafar

American University in Cairo, Cairo, Egypt

Paper No. DETC2010-28393, pp. 745-753; 9 pages
  • ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 1: 36th Design Automation Conference, Parts A and B
  • Montreal, Quebec, Canada, August 15–18, 2010
  • Conference Sponsors: Design Engineering Division and Computers in Engineering Division
  • ISBN: 978-0-7918-4409-0 | eISBN: 978-0-7918-3881-5
  • Copyright © 2010 by ASME


Automated Optical Inspection (AOI) systems are rapidly replacing slow and tedious manual inspections of Printed Circuit Boards (PCBs). In an AOI system, a minicamera traverses the PCB in a pre-defined travel path, snapping shots of all the PCB components or nodes, at pre-defined locations. The images are then processed and information about the different nodes is extracted and compared against ideal standards stored in the AOI system. This way, a flawed board is detected. Minimizing both the number of images required to scan all the PCB nodes, and the path through which the camera must travel to achieve this, will minimize the image acquisition time and the traveling time, and thus the overall time of inspection. This consequently both reduces costs and increases production rate. This work breaks down this problem into two sub-problems: The first is a clustering problem; the second a travelling salesman sequencing problem. In the clustering problem, it is required to divide all the nodes of a PCB into the minimum number of clusters. The cluster size is constrained by the given dimensions of the camera’s scope or Field of Vision (FOV). These dimensions determine the dimension of the inspection windows. It is thus required to find the minimum number of inspection windows that will scan all the nodes of a PCB, and their locations. Genetic algorithms are applied in a two-step approach with special operators suited for the problem. A continuous Genetic Algorithm (GA) is applied to find the optimum inspection window locations that cover one node and as many other nodes as possible. A discrete GA is then applied to eliminate redundant inspection windows leaving the minimum number of windows that cover all nodes throughout the PCB. In the second sub-problem, an Ant Colony Optimization (ACO) method is used to find the optimum path between the selected inspection windows. The method proposed in this paper is compared against relevant published work, and it is shown to yield better results.

Copyright © 2010 by ASME



Interactive Graphics


Country-Specific Mortality and Growth Failure in Infancy and Yound Children and Association With Material Stature

Use interactive graphics and maps to view and sort country-specific infant and early dhildhood mortality and growth failure data and their association with maternal

Citing articles are presented as examples only. In non-demo SCM6 implementation, integration with CrossRef’s "Cited By" API will populate this tab (http://www.crossref.org/citedby.html).

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In