Computer Vision for Electronics Manufacturing

1. Front Matter

   Pages i-xvi

   PDF

2. Introduction and Organization of the Book

   1. Introduction and Organization of the Book

      • L. F. Pau

      Pages 1-4

3. Applications and Systems Aspects

   1. Front Matter

      Pages 5-5

      PDF

   2. Vision System Components

      • L. F. Pau

      Pages 7-31

   3. Imaging Microscopes for Microelectronics

      • L. F. Pau

      Pages 33-52

   4. Metrology in Electronic Devices and Substrates

      • L. F. Pau

      Pages 53-59

   5. Inspection of Integrated Circuits and Gate Arrays

      • L. F. Pau

      Pages 61-86

   6. Sensor Fusion for Integrated Circuit Testing

      • L. F. Pau

      Pages 87-104

   7. Wafer Inspection

      • L. F. Pau

      Pages 105-115

   8. Mask Repair and Inspection

      • L. F. Pau

      Pages 117-125

   9. Knowledge-Based Processing

      • L. F. Pau

      Pages 127-131

   10. Design Rule Verification

       • L. F. Pau

       Pages 133-139

   11. Printed Circuit Board (PCB) Inspection

       • L. F. Pau

       Pages 141-160

   12. Inspection for Assembly Tasks

       • L. F. Pau

       Pages 161-185

   13. Knowledge-Based Printed Circuit Board Manufacturing

       • L. F. Pau

       Pages 187-206

4. Vision Algorithms for Electronics Manufacturing

   1. Front Matter

      Pages 207-207

      PDF

   2. Image Quantization and Thresholding

      • L. F. Pau

      Pages 207-213

   3. Geometrical Corrections

      • L. F. Pau

      Pages 215-219

   4. Image Registration and Subtraction

      • L. F. Pau

      Pages 221-231

   5. Edge and Line Detection

      • L. F. Pau

      Pages 233-241

DEFECT PROPORTION OF DETECTION INITIAL RATE DETECTION RATE INSPECTOR 3 COMPLEXITY OF TIMES PAN OF PERFORMING o~ ________________________ o~ ______________________ __ -;. INSPECTION TASK -;. VISUAL INSPECTION Fagure 1. Trends in relations between the complexity of inspection tasks, defect detection rates (absolute and relative), and inspection time. Irrespective of the necessities described above, and with the excep­ tion of specific generic application systems (e.g., bare-board PCB inspection, wafer inspection, solder joint inspection, linewidth measure­ ment), vision systems are still not found frequently in today's electronics factories. Besides cost, some major reasons for this absence are: 1. The detection robustness or accuracy is still insufficient. 2. The total inspection time is often too high, although this can frequently be attributed to mechanical handling or sensing. 3. There are persistent gaps among process engineers, CAD en­ gineers, manufacturing engineers, test specialists, and computer vision specialists, as problems dominate the day-to-day interac­ tions and prevent the establishment of trust. 4. Computer vision specialists sometimes still believe that their contributions are universal, so that adaptation to each real problem becomes tedious, or stumbles over the insufficient availabIlity of multidisciplinary expertise. Whether we like it or not, we must still use appropriate sensors, lighting, and combina­ tions of algorithms for each class of applications; likewise, we cannot design mechanical handling, illumination, and sensing in isolation from each other.

• Sensor
• Signal
• Wafer
• algorithms
• circuit
• complexity
• computer
• computer vision
• electronics
• image processing
• integrated circuit
• logic
• manufacturing
• model
• transmission

• Technical University of Denmark, Lyngby, Denmark

  L. F. Pau

• University of Tokyo, Tokyo, Japan

  L. F. Pau

Policies and ethics