• Journal of the Korean Society for Precision Engineering
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• v.15 no.5
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• pp.9-18
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• 1998

The components with J-lead. which are more integrated and smaller than ones with Gull-wing. are rapidly being used in electronic board such as the PCB, for they have the advantage of occupying a small space compared to the other components. However, the development of inspection system for these new components is not so rapid as component development. Component-inspection with J-lead using vision system is difficult because they are hidden from camera optical axis. X-ray inspection, which has the advantage of inspecting the inside of solder state, is used to J-lead inspection. However. it is high cost and dangerous by leaking out X-ray compared to vision system. Therefore, in this paper, we design vision system suited to J-lead inspection and then propose algorithm which have flexibility in mount and rand error.

• Proceedings of the KIEE Conference
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• 2003.11b
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• pp.291-294
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• 2003

In this paper, 2D and 3D inspection algorithm for printed solder on PCB is introduced. The aim of inspection is the detection of error such as rich solder poor solder and missing solder. For Inspection, laser distance sensor is used. For 2D inspection, laser image that is created by normalizing laser data between 0 and 255 are used. Reference Image is made using gerber file. Image processing algorithm is used for 2D inspection. By adding thickness of metal stencil to laser image, volume for solder can be calculated and 3D inspection is carried out.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.81-84
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• 2002

This paper presents the real-time PCB(Printed circuit board) inspection system that can detect thin open/short error using the line scan camera. After a overall introduction of our system, the outline of our inspection methods are described. The goal of our inspection system is the real time and detailed inspection using the line scan camera. To perform inspection processing in real-time, we utilize double buffering structure. In order to solve the problem of unexpectable pixels of PCB, we propose melting process which eliminates unexpectable pixels of PCB. The design and development of our prototype of PCB ins- pection system is discussed and test results are presented to show the effectiveness of the developed inspection algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.2
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• pp.45-50
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• 1990

A replacement policy with repair cost limit is discussed. When a system fails, the repair cost is estimated by inspection and repair is then undertaken if the estimated cost is less than a predetermined limit L ; otherwise the system is replaced. After repair, the system is as good as new with probability(l-p) or is minimally repaired with probability p. It is assumed that repair cost can not be estimated exactly because of inspection error. When the failure time follows a Weibull distribution and repair cost a normal distribution, the value of repair cost limit minimizing the expected cost rate is shown to be finite and unique.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.61-62
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• 2006

A new neural network classifier is proposed for the automatic real-time surface inspection of high-speed cold steel strips having 11 different types of defects. 46 geometrical and gray-level features are extracted for the defect classification. 3241 samples of Posco's Kwangyang steel factory are used for training and testing the neural network classifier. The developed classifier produces plausible 15% error rate which is much better than 20-30% error rate of human vision inspection adopted in most of domestic steel factories.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.4 s.193
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• pp.76-83
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• 2007

A new neural network classifier is proposed for the automatic real-time surface inspection of high-speed cold steel strips having 11 different types of defects. 46 geometrical and gray-level features are extracted for the defect classification. 3241 samples of Posco's Kwangyang steel factory are used for training and testing the neural network classifier. The developed classifier produces plausible 15% error rate which is much better than 20-30% error rate of human vision inspection adopted in most of domestic steel factories.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.4
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• pp.241-249
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• 2015

The purpose of this research is to develop the pattern recognition algorithm based on smart camera for inspection automation, and including external surface state of molding parts or optical parts. By performance verification, this development can be applied to establish for existing reflex data because inputting surface badness degree of scratch's standard specification condition directly. And it is pdssible to distinguish from schedule error of badness product and normalcy product within schedule extent after calculating the error comparing actuality measurement reflex data and standard reflex data mutually. The proposed technology cab be applied to test for masearing of the smallest 10 pixel unit. It is illustrated the relibility pf proposed technology by an experiment.

• Journal of the Korea Safety Management & Science
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• v.19 no.3
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• pp.49-58
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• 2017

This paper suggests a specific model that could efficiently improve the interaction and the interface between MES(Manufacturing Execution System) server and POP(Point of Production) terminal through electronic document server and electronic pen, bluetooth receiver and form paper in disassembly and process inspection works. The proposed model shows that the new method by electronic document automation system can more efficiently perform to reduce processing time for maintenance work, compared with the current approach by handwritten processing system. It is noted in case of the method by electronic document automation system that the effects of proposed model are as follows; (a) While the processing time per equipment for maintenance by the current method was 300 minutes, the processing time by the new method was 50 minutes. (b) While the processing error ratio by the current method was 20%, the error ratio by the new method was 1%.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.5
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• pp.104-111
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• 2009

A ship engine operator should compensate the crankshaft assembly of ship engine after inspecting crankshaft deflection error in the crank throw regularly to avoid engine vibration and abrasions. In the previous method, the operator enters the bed plate and measures crankshaft deflection using dial gauge on rotating crankshaft manually. However, this method can cause dangerous situation to the operator as well as uncomfortable in an inferior environment. In order to solve the problems, this paper studies the method which makes the operator measure the error outside of the bed plate. In this paper, it is suggested that BlueTooth wireless communication transfers the error data to the outer standing operator with digitalized crankshaft deflection inspection device developed in this paper. So, the wireless measurement system is developed and applied to a medium-speed marine engine through size-miniaturization. After applying test, the developed inspection device showed that it provides much safe and ease inspection method. Furthermore, in the result, the measuring accuracy is more improved.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.434-437
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• 2003

Evaluation or the patterning accuracy of e-beam lithography machines requires a high precision inspection system that is capable of measuring the true xy-locations of fiducial marks generated by the e-beam machine under test. Fiducial marks are fabricated on a single photo mask over the entire working area in the form of equally spaced two-dimensional grids. In performing the evaluation, the principles of self-calibration enable to determine the deviations of fiducial marks from their nominal xy-locations precisely, not being affected by the motion errors of the inspection system itself. It is. however, the fact that only repeatable motion errors can be eliminated, while random motion errors encountered in probing the locations of fiducial marks are not removed. Even worse, a random error occurring from the measurement of a single mark propagates and affects in determining locations of other marks, which phenomenon in fact limits the ultimate calibration accuracy of e-beam machines. In this paper, we describe an uncertainty analysis that has been made to investigate how random errors affect the final result of self-calibration of e-beam machines when one uses an optical inspection system equipped with high-resolution microscope objectives and a precision xy-stages. The guide of uncertainty analysis recommended by the International Organization for Standardization is faithfully followed along with necessary sensitivity analysis. The uncertainty analysis reveals that among the dominant components of the patterning accuracy of e-beam lithography, the rotationally symmetrical component is most significantly affected by random errors, whose propagation becomes more severe in a cascading manner as the number of fiducial marks increases