• Journal of the Korea Safety Management & Science
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• v.21 no.4
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• pp.67-74
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• 2019

Visual inspection is regarded as one of the critical activities for quality control in a manufacturing company. it is thus important to improve the performance of detecting a defective part or product. There are three probable working modes for visual inspection: fully automatic (by automatic machines), fully manual (by human operators), and semi-automatic (by collaboration between human operators and automatic machines). Most of the current studies on visual inspection have been focused on the improvement of automatic detection performance by developing a better automatic machine using computer vision technologies. However, there are still a range of situations where human operators should conduct visual inspection with/without automatic machines. In this situation, human operators'performance of visual inspection is significant to the successful quality control. However, visual inspection of components assembled into a mobile camera module belongs to those situations. This study aims to investigate human performance issues in visual inspection of the components, paying more attention to human errors. For this, Abstraction Hierarchy-based work domain modeling method was applied to examine a range of direct or indirect factors related to human errors and their relationships in the visual inspection of the components. Although this study was conducted in the context of manufacturing mobile camera modules, the proposed method would be easily generalized into other industries.

• Journal of the Semiconductor & Display Technology
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• v.16 no.2
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• pp.1-8
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• 2017

The visual inspection of electronic parts consists of two steps: automatic visual inspection and verification inspection. In the stage of a verification inspection, the human inspector sequentially inspects all the areas which detected in the automatic inspection. In this study, we propose an algorithm to determine the order of verification inspection by Bayes inference well known in the field of machine learning. This is a method of prioritizing a region estimated to have a high probability of defect using experience data of past inspection. This algorithm was applied to the visual inspection of ultraviolet filters to verify its effectiveness. As a result of the comparison experiment, it was confirmed that the verification inspection can be completed 30% of the conventional method by adapting proposed algorithm.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.05a
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• pp.396-399
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• 2004

This study was performed to develop necessary Visual Inspection System for the PSC Bridges precision safety diagnosis which to enhance the efficiency and accuracy of visual inspection by using mobile PC and adopted IT. This system was constructed to the automatic visual inspection map generating program and the Visual Inspection System using mobile PC that predicted high efficiency.

• Journal of the Semiconductor & Display Technology
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• v.13 no.3
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• pp.1-6
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• 2014

Visual defect inspection for electronics parts manufacturing processes is comprised of 2 steps - automatic visual inspection by machine and inspection by human inspectors. It is necessary that spatial points which were detected by the machine should be adequately clustered for subsequent human inspection. This research deals with the spatial clustering algorithm for the purpose of process productivity improvement. Distribution based clustering is newly developed and experimentally confirmed to show better clustering efficiency than existing algorithm - area based clustering.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.88.3-88
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• 2001

In this paper, an on-line multi-sensor visual inspection technique for seamless steel pipe´s straightness is developed. The basic principle of the visual measuring method is detailed. The modeling of visual sensor, measurement system and data processing are presented. In order to test the accuracy of the multi-sensor visual inspection, an experiment inspecting the straightness of a 1500mm long seamless steel pipe is made. The experiment results show that the visual inspection technique can achieve on-line measurement and offers high precision and stability.

• Proceedings of the CALSEC Conference
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• 2003.09a
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• pp.72-77
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• 2003

Visual inspection works are very important part of facility maintenance and management life cycle as a step of creating base data for decision making and maintenance and repair. But currently, visual inspection works have been performed unefficiently and unreliably as works on hand, duplication of works, decisions of defect state, unutilization of inspection history, lack of professional and so on. In this research, we developed visual inspection system that processes inspection work efficiently and provides reliability of inspection output, as a target of bridges, tunnels, underground roadway on national road. We defined problems through visual inspection work analysis, examined the solutions and reflected to functional design of system. We will plan to utilize this system in HMCS(Highway Maintenance and Construction Service).

• Journal of the Korea Society of Computer and Information
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• v.21 no.6
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• pp.71-76
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• 2016

In this paper, we propose the mobile visual inspection information system using DGPS and portable range finder for levee safety inspection. Instead of existing visual inspection management method that is stored hand-written data, this system is designed to manage directly the visual inspection information using mobile devices in the field of levee. And through extracting accurate DGPS coordinates information about damage location of levee, this system is developed to ensure efficiency for the main task arising from the levee site such as inspection, maintenance and reinforcement. Furthermore, when damage has occurred at the point that inspector is not able to approach, this system can record the damage site data correctly, by converting data such as position, orientation and height of the damage point into the World Geodetic System coordinates. The position, orientation and height data was extracted automatically through the DGPS and portable range finder. And by applying the augmented reality method, this system was implemented for inspector to revisit the point of damage easily in order to perform the management, maintenance and reinforcement of the levee later.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.18 no.2
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• pp.75-84
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• 2014

Objectives Eyes, one of visual inspection regions, present important clues to pathological patterns including deficiency and excess patterns to the clinicians. The purpose of this study was to develop Eyes Inspection Questionnaire (EIQ) and to examine which items among the EIQ were more predictive of clinicians' determination for the deficiency and excess patterns. Methods Nine questionnaire items for Visual Inspection of Eyes were extracted through the literature review. These items were presented to the 4 Korean medical doctors who are specialized in visual inspection to conduct the Delphi method. The Korean medical doctors were asked to rate the importance of each items for the corresponding Visual Inspection of Eyes, using a Likert 5-point scale(the 3 points of importance as a cut-off point). Then, out of 75 photographs submitted to the Society of HyungSang Medicine in 2009, 30 portrait pictures were selected as samples. The samples were copied to make 60 sample pictures, and then randomly assigned to 4 clinicians. The 4 clinicians evaluated the 60 samples for excess and deficiency of the eyes and were asked to check the 6 questionnaire items. The results were recorded as 5-points-scale, and their average and standard deviations were calculated. Intra- class reliability test and multi regression test were performed using SPSS 13. Results Intra-class correlation coefficient (ICC) was between 0.750 to 0.841 (P<0.05). Indices for visual inspection of the eyes were: endowment of the bone structure around the eyes; brightness of the eyes; upward deviation of the eyes; eye shapes; and definition of iris. 76.92% of deficiency symptom patterns and 86.42% of the excess symptom patterns matched the patterns predicted by the visual inspection of the eyes, according to the frequency analysis. According to the multiple regression analysis, were significantly related to the excessive symptoms, and to the deficiency symptoms. Conclusion This study is the first attempt of development for checklist of excess and deficiency of Visual Inspection of Eyes and quantitative measurement of excess and deficiency using the Visual Inspection of Eyes by the visual inspection experts. Still, additional studies are needed regarding the relationship visual inspection methods have with existing standards of diagnosis.

• The Journal of the Society of Korean Medicine Diagnostics
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• v.15 no.3
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• pp.235-244
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• 2011

Objectives: There are four types of diagnostic methods in Oriental medicine, and visual inspection is the first method among them. This study was written in order to complement further understanding on visual inspection. Methods: The authors reviewed a word related with visual inspection in Nei-Ching. The authors researched static words such as bigger/smaller, longer/shorter, slower/faster, curved/straight, one-sided/fair, and groove/uplift, and active words such as extension and contraction, shake, tremor, slow, fast, walk, run, standing, lying, and sitting related with visual inspection in Nei-Ching. Results: The static words linked with visual inspection are related with skin, muscles, fat, and especially the liver, stomach, and large intestine. The active words linked with visual inspection are related with movement of muscles, fat, and bone. Conclusion: In this study, the authors provided further understanding on visual inspection in Nei-Ching. However, there was no clear reference point about appearances and movements.

• Journal of the Ergonomics Society of Korea
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• v.30 no.5
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• pp.645-650
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• 2011

Objective: The aim of this study is to design a sampling inspection plan with human error which is changing according to inspection time. Background: Typical sampling inspection plans have been established typically based on an assumption of the perfect inspection without human error. However, most of all inspection tasks include human errors in the process of inspection. Therefore, a sampling inspection plan should be designed with consideration of imperfect inspection. Method: A model for single sampling inspection plans were proposed for the cases that visual inspection error rate is changing according to inspection time. Additionally, a sampling inspection plan for an optimal inspection time was proposed. In order to show an applied example of the proposed model, an experiment for visual inspection task was performed and the inspection error rates were measured according to the inspection time. Results: Inspection error rates changed according to inspection time. The inspection error rate could be reflected on the single sampling inspection plans for attribute. In particular, inspection error rate in an optimal inspection time may be used for a reasonable single sampling plan in a practical view. Conclusion: Human error rate in inspection tasks should be reflected on typical single sampling inspection plans. A sampling inspection plan with consideration of human error requires more sampling number than a typical sampling plan with perfect inspection. Application: The result of this research may help to determine more practical sampling inspection plan rather than typical one.