• KIPS Transactions on Software and Data Engineering
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• v.4 no.2
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• pp.65-70
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• 2015

In the PCB(Printed Circuit Board) manufacturing industry, the yield is an important management factor because it affects the product cost and quality significantly. In real situation, it is very hard to ensure a high yield in a manufacturing shop because products called chips are made through hundreds of nano-scale manufacturing processes. Therefore, in order to improve the yield, it is necessary to analyze main fault process and equipment that cause low PCB yield. This paper proposes a systematic approach to discover fault-causing processes and equipment by using a logistic regression and a stepwise variable selection procedure. We tested our approach with lot trace records of real work-site. A lot trace record consists of the equipment sequence that the lot passed through and the number of faults for each fault type in the lot. We demonstrated that the test results reflected the real situation of a PCB manufacturing line.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.1
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• pp.35-42
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• 2016

The core of the machine vision that is frequently used at the pre/post-production stages is a marker alignment technology. In this paper, a method to detect the angle and position of a product at high speed by use of a unique pattern present in the marker stamped on the product, and calibrate them is proposed. In the proposed method, to determine the angle and position of a marker, the candidates of the marker are extracted by using a variation of the integral histogram, and then clustering is applied to reduce the candidates. The experimental results revealed about 5s 719ms improvement in processing time and better precision in detecting the rotation angle of a product.