Performance Measurement of Thresholding Algorithms in Printed Circuit Board Inspection System

Author(s):  
Ismail Ibrahim ◽  
Syed Abdul Rahman Syed Abu Bakar ◽  
Musa Mohd Mokji ◽  
Kamal Khalil ◽  
Zulkifli Md. Yusof ◽  
...  
Author(s):  
Tatang Rohana Cucu

Pengujian kualitas menggunakan teknik pengolahan citra dan kecerdasan tiruan banyak diterapkan dalam berbagai industri, misalnya industri tekstil, perakitan kendaraan, makanan, minuman, perakitan elektronik, dan lain – lain. Pengujian model ini sering disebut dengan istilah Automated Visual Inspection System (AVIS) atau dalam bahasa Indonesia Sistem Inspeksi Visual Otomatis (SIVO). Penelitian ini mengacu pada model sistem inspeksi, di mana objek pengujiannya adalah keping Printed Circuit Board (PCB). Banyak penelitian tentang pengujian PCB yang sudah dilakukan, tetapi masih banyak yang belum memberikan hasil yang optimum, diantaranya waktu akses yang masih lambat, keakuratan data masih rendah, dan tingkat kesalahan yang masih tinggi. Berdasarkan hasil penelitian dan pengujian yang sudah dilakukan, model ANFIS sangat layak dijadikan sebagai model inferensi kecerdasan buatan dalam sistem yang berbasis inspeksi otomatis khususnya menguji kualitas keping PCB, karena terbukti model ANFIS dengan model hybrid trapesium mf memiliki tingkat kesalahan yang sangat kecil yaitu 4.0186e-007 dan untuk tingkat akurasi pengujian datanya mencapai 99%. 


CIRP Annals ◽  
1987 ◽  
Vol 36 (1) ◽  
pp. 399-402 ◽  
Author(s):  
Tadanori Komatsu ◽  
Shinichi Uno ◽  
Mitsuji Inoue ◽  
Shingo Sekiguchi ◽  
Akira Kobayashi

Optik ◽  
2014 ◽  
Vol 125 (17) ◽  
pp. 4929-4931 ◽  
Author(s):  
Yu Wang ◽  
Mingquan Wang ◽  
Zhijie Zhang

1989 ◽  
Author(s):  
Shiaw-Shian Yu ◽  
Wen-Chin Cheng ◽  
Chris S. C. Chiang

1995 ◽  
Vol 7 (3) ◽  
pp. 225-229
Author(s):  
Shunichiro Oe ◽  
◽  
Kennichi Kaida ◽  
Daisuke Nagai ◽  
Mituo Nakamura ◽  
...  

This paper deals with a new inspection system of soldering joint on printed circuit board by using neural network. A sensor unit of this system consists of a semiconductor laser unit, four PSDs, and a pin photo-diode. We can obtain four types of images which are called height image, PSD brightness image, vertical image and vector image, by using four sensor units. We extract the features which show the state of soldering joint from these images and develop an inspection system using the neural networks constructed for the features and the state of soldering joint.


2012 ◽  
Vol 268-270 ◽  
pp. 1393-1397
Author(s):  
Chien Chih Wang

To improve the printed circuit board (PCB) manufacturing process, it is important to have an automatic inspection system that classifies information regarding defects in solder joints. This paper proposes a quality decision system for solder joint defect classification on a PCB. An experiment was conducted to demonstrate the application of the system. The results showed that the inspection accuracy reached 94%, which is superior to the results achieved by other methods. The results of this study provide an effective solution for the inspection of the solder joint quality.


Author(s):  
Zuwairie Ibrahim ◽  
Noor Khafifah Khalid ◽  
Ismail Ibrahim ◽  
Mohamad Shukri Zainal Abidin ◽  
Musa Mohd Mokji ◽  
...  

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