• Journal of the Semiconductor & Display Technology
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• v.16 no.3
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• pp.53-58
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• 2017

Recently, advance in technology have increased the importance of visual inspection in semiconductor inspection areas. In PCB visual inspection, accurate line estimation is critical to the accuracy of the entire process, since it is utilized in preprocessing steps such as calibration and alignment. We propose a line estimation method that is differently weighted for the line candidates using a histogram of gradient information, when the position of the initial approximate corner points is known. Using the obtained line equation of the outline, corner points can be calculated accurately. The proposed method is compared with the existing method in terms of the accuracy of the detected corner points. The proposed method accurately detects corner points even when the existing method fails. For high-resolution frames of 3.5mega-pixels, the proposed method is performed in 89.01ms.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.6
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• pp.22-29
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• 2022

In this study, an automatic marking system for fabric inspection machines was developed. The main objectives of the study were to promote intelligence and automation for the inspection process, as well as to increase textile industrial productivity. Generally, when a worker manually inspects and marks a fabric, human error and reduced efficiency are unavoidable. To overcome these problems, we developed an automatic marking system that uses robots. This system incorporates a vision camera to automatically recognize defects, and an optical fiber sensor to detect the side of the fabric. To verify the performance, the control system sends a command directly to the robot to mark the fabric. Finally, the actual production confirmed that the proposed system could perform the desired motion.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.298-301
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• 1996

This paper addresses the effects of an imperfect production process on the optimal production quantity and quality inspection policies. The system is assumed to deteriorate during the production process. The results are either defective products or machine breakdown whether multiple quality inspection is worth or not. Furthermore, when multiple inspection policy is adopted, the optimal inspection schedule is shown to be equally spaced throughout the production cycle. Exact solution and approximation of the optimal production quantity and approximation of the optimal number of inspection are provided. Finally, to better understand the model of this paper, comparisons between this model and classical EMQ model are provided.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.51-56
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• 2000

This study is to implement automatic inspection system of motor body panel by visual system. since it is inefficient to examine adhesion condition of components with the naked eye, image processing algorithm is presented to replace the existing manual inspection process with an automatic inspection process the developed automatic inspection system presents tile examination method of the adhesion condition of components with a pixed camera, which leads to an increase of the productivity and a reduction of manufacturing cost

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.1141-1149
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• 2009

In Bone Mineral Density(BMD) measurements, accuracy and precision must be superior in order to know the small changes in bone mineral density and actual biological changes. Therefore the purpose of this study is to increase the reliability of bone mineral density inspection through appropriate management of image quality from machines and inspectors. For the machine management method, the recommended phantom from each bone mineral density machine manufacturer was used to take 10~25 measurements to determine the standard amount and permitted limit. On each inspection day, measurements were taken everyday or at least three times per week to verify the whether or not change existed in the amount of actual bone mineral density. Also evaluations following Shewhart control chart and CUSUM control chart rules were made for the bone mineral density figures from the phantoms used for measurements. Various forms of management became necessary for machine installation and movement. For the management methods of inspectors, evaluation of the measurement precision was conducted by testing the reproducibility of the exact same figures without any real biological changes occurring during reinspection. There were two measurement methods followed: patients were either measured twice with 30 measurements or three times with 15 measurements. An important point to make regarding measurements is that after the first inspection and any other inspection following, the patient was required to come off the inspection table completely and then get back on for any further measurements. With a 95% confidence level, the precision error produced from the measurement bone mineral figures produced a precision error of 2.77 times the minimum of the biological bone mineral density change (Least significant change: LSC). In order to assure reliability in inspection, there needs to be good oversight of machine management and measurer for machine operation and inspection error. Accuracy error in machines needs to be reduced to under 1% for scientific development in bone mineral density machines.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.6
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• pp.370-376
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• 2016

Manufacturing data analysis and its applications are getting a huge popularity in various industries. In spite of the fast advancement in the big data analysis technology, however, the manufacturing quality data monitored from the automated inspection system sometimes is not reliable enough due to the complex patterns of product quality. In this study, thus, we aim to define the level of trusty of an automated quality inspection system and improve the reliability of the quality inspection data. By correlation analysis and feature selection, this paper presents a method of improving the inspection accuracy and efficiency in an SVM-based automatic product quality inspection system using thermal image data in an auto part manufacturing case. The proposed method is implemented in the sealer dispensing process of the automobile manufacturing and verified by the analysis of the optimal feature selection from the quality analysis results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.813-815
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• 2011

This study inspects the fault of the vehicle forming assembly and the assembly state of components at high speed and high degree of precision. This study also proposes the general inspection system capable of adapting to a number of products. The inspection program is composed of the fault inspection algorithm to examine the surface of the object and the state of the assembly and the high speed procession algorithm for the real time examination. The fault inspection algorithm is processed largely by a method using average of pixel in ROI and a method dividing the area and checking the presence of the object. Lastly, we verified the efficiency of the sysytem through the evaluation of its accuracy and processing time.

• Magazine of the Korea Institute for Structural Maintenance and Inspection
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• v.17 no.1
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• pp.30-42
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• 2013

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.10a
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• pp.148-148
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• 2003

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.691-692
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• 2008