Abstract
The new visual inspection systems techniques using real time machine vision replace the human visual manual inspection on PCB flux defects, which brings harmful effects on the board which may come in the form of corrosion and can cause harm to the assembly. In short, it brings improvement in Printed Circuit Boards (PCB) production quality, principally concerning the acceptance or rejection of the PCB boards. To develop new algorithm in image processing which detects flux defect at PCB board during re-flow process and achieve good accuracy of the PCB quality checking. The machine will be designed and fabricated with the total automation control system with mechanical PCB loader/un-loader, pneumatic system handler with vacuum cap, vision inspection station and final classification station (accept or reject). The image processing system is based on shape (pattern) and color image analysis techniques with Matrox Imaging Library. The shape/texture of the PCB pins is analyzed by using pattern matching technique to detect the PCB flux defect area. The color analysis of the flux defect in a PCB boards are processed based on their red color pixel percentage in Red, Green and Blue (RGB) model. The red color filter band mean value of histogram is measured and compared to the value threshold to determine the occurring on the PCB flux defects. The system was tested with PCB boards from factory production line and achieved PCB board flux defects sorting accuracy at 86.0% based on proposed pattern matching technique combined with red color filter band histogram.
Highlights
Visualize by human eye because it’s liquid and transparent
The system was tested with Printed Circuit Boards (PCB) boards from factory production line and achieved PCB board flux defects sorting accuracy at 86.0% based on proposed pattern matching technique combined with red color filter band histogram
Mashohor et al (2004), this study presents the first prototype of automating a low-cost printed circuit (PCB) inspection on physical defects through the development of a technique for image detection using Genetic Algorithm (GA)
Summary
Visualize by human eye because it’s liquid and transparent. The result, obtained based on the proposed. The main disadvantage of manual inspection of PCB technique is possibly be applied in automated PCB defects are human errors, inconsistent grading and labour manufacturing process. The machine will be designed and fabricated with “PC-Based Machine Vision”. To identify the fatal the Total Automation Control System with mechanical defects the system uses a connectivity approach, it finds PCB loader/un-loader, pneumatic system handler with any type of error like: PCB board printing and labeling, vacuum cap, vision inspection station and final scratches, marking on components, components classification station (accept or reject). Computer Vision techniques were used to develop focus is on PCB flux defect, which is very difficult to an automatic visual inspection of PCB boards, which. No., Jalan SP2/2, Serdang Perdana, 43300 Sri Kembangan, Selangor, Malaysia
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