• Journal of Fashion Business
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• v.7 no.4
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• pp.26-42
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• 2003

On-line clothes sale are on the increase, and the returns(for replacements or refunds) of the clothes are also increasing. Many studies on off-line consumers' complaints were made before, but few studies on the returns of clothes sold on-line have been made. From this viewpoint, this study was conducted to know what effect returns of clothes sold on-line have on their brands. Therefore, this study was first focused on the factors affecting complaint acts(return intention or return acts) such as lack of information and recognition of product, delivery errors and product defects concerning on-line sales, and second investigated the changes of buyers' attitude toward the brand following the their acts of returning the buyers, and third looked into the changes of on-line buyers' attitude toward the brand. The study is carried out by subdividing the objects of the study into return action(replacement, refundment) and purchasers who experienced return intention. Such experience is demonstratively analyzed to find how it has affected the attitude toward the brand. The study comes up with the following outcomes. First, the effect factor causing complaint action(return action, return intention) on-line is shown as the lack of the information and recognition of the product. Second, it is revealed that the effect factor causing complaint(return action, return intention) does not lie in an error in delivery or a defect of a product. Third, the positive response of a brand to a return action does not raise the repurchasing intention and positive attitude of purchasers who experienced returning a product, but lowers their private complaint action intention. Fourth, the repurchase intention of purchasers who experienced return intention for the brand is lowered, but their negative attitude and private complaint action intention is not raised.

• Transactions of Materials Processing
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• v.19 no.8
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• pp.486-493
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• 2010

A shape error of the sheet metal product made by a flexible stretch forming process is occurred by a various forming parameters. A die used in the flexible stretch forming is composed of a punch array to obtain the various objective surfaces using only one die. But gaps between the punches induce the shape error and the defect such as a scratch. Forming parameters of the punch size and the elastic pad to prevent the surface defect must be considered in the flexible die design process. In this study, tendency analysis of shape error according to the forming parameters in the flexible stretch process is conducted using a finite element method. Three forming parameters, which are the punch size, the objective curvature radius and the elastic pad thickness, are considered. Finite element modeling using the punch height calculation algorithm and the evaluation method of the shape error, which is a representative value for the formability of formed surface, are proposed. Consequently, the shape error is in proportion to the punch size and is out of proportion to the objective curvature radius and the elastic pad thickness.

• Proceedings of the KIEE Conference
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• 2007.11c
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• pp.112-116
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• 2007

If any of the set parameters such as the environment temperature, mold temperature are not maintained at a consistent level, the fail rate of injection molding products is increased. The price of the injection molding machine is very high, so in order to maximize the utilization of the machine that is required the production of a number of different products with minimum fail rate using a single machine. To prevent the defect products by an inspection process with perfect quality is very important to minimizing production of defect products in the molding process. Vision inspection systems are widely utilized in various manufacturing industries for quality assurance purposes. The vision inspection system consists of CCD camera and lighting system to capture the image of the subject of inspection, an image comparison algorithm using to determine the pass/fail of the products, and mechanical devices for the operation of the whole system. This research focuses on the development of the vision inspection system to process the inspection of an automobile parts. We developed a mechanical devices for the inspection of the injection molding products and an image comparison algorithm to determine the pass/fail result of the inspection based on the molding image and the accepted product image.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.24-29
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• 1996

The seniconductor, which is precision product, requires many inspection processes. The surface conditions of the semiconductor chip effect on the functions of the semiconductors. The defects of the chip surface is crack or void. Because general inspection method requires many inspection processes, the inspection system which searches immediately and preciselythe defects of the semiconductor chip surface. We propose the inspection method by using the computer vision system. This study presents an image processing algorithm for inspecting the surface defects(crack, void)of the semiconductor test samples. The proposed image processing algorithm aims to reduce inspection time, and to analyze those experienced operator. This paper regards the chip surface as random texture, and deals with the image modeling of randon texture image for searching the surface defects. For texture modeling, we consider the relation of a pixel and neighborhood pixels as noncasul model and extract the statistical characteristics from the radom texture field by using the 2D AR model(Aut oregressive). This paper regards on image as the output of linear system, and considers the fidelity or intelligibility criteria for measuring the quality of an image or the performance of the processing techinque. This study utilizes the variance of prediction error which is computed by substituting the gary level of pixel of another texture field into the two dimensional AR(autoregressive model)model fitted to the texture field, estimate the parameter us-ing the PAA(parameter adaptation algorithm) and design the defect detection filter. Later, we next try to study the defect detection search algorithm.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.2
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• pp.86-92
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• 2021

Usually, the die-cast components used in small mobile devices require finishing processes, such as computer numerically controlled coating. In such cases, porosity is the most important defect. The shape of the molten aluminum that passes through the runner and gate in a mold is the one of the factors that influences gas porosity. To define the spurt index, which numerically indicates the shape of molten aluminum after the gate, Reynolds number and Ohnesorge number are used. Before die fabrication, computer-aided engineering analysis is performed to optimize the filling pattern. Finally, X-ray and surface inspection are performed after casting and machining to evaluate how the spurt index affects porosity and other product parameters. Based on the results obtained herein, a new gating system design process is suggested.

• Journal of the Semiconductor & Display Technology
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• v.21 no.2
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• pp.74-84
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• 2022

As the semiconductor industry develops, the difficulty of newly required process technology becomes difficult, and the importance of production yield and product reliability increases. As an effort to minimize yield loss in the manufacturing process, interests in the process defect process for facility diagnosis and defect identification are continuously increasing. This research observed the plasma condition changes in the multi oxide/nitride layer deposition (MOLD) process, which is one of the 3D-NAND manufacturing processes through optical emission spectroscopy (OES) and monitored the result of whether the change in plasma characteristics generated in repeated deposition of oxide film and nitride film could directly affect the film. Based on these results, it was confirmed that if a change over a certain period occurs, a change in the plasma characteristics was detected. The change may affect the quality of oxide film, such as the film thickness as well as the interfacial surface roughness when the oxide and nitride thin film deposited by plasma enhenced chemical vapor deposition (PECVD) method.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.239-249
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• 2013

The role of software process is getting more important to make good quality softwares. One of the measures to improve the software process is Defect Removal Efficiency(DRE). DRE gives a measure of the development team ability to remove defects prior to release. It is calculated as a ratio of defects resolved to total number of defects found. Software Engineering Levels are usually decided by CMMI Model. The model is designed to help organizations improve their software product and service development, acquisition, and maintenance processes. The score of software engineering levels can be calculated by CMMI model. The levels are composed of the three groups(absent, average, and advanced). This study is to find if there is any difference among the three categories in term of the result of software engineering levels on DRE. We propose One way ANOVA to analyze influence of software engineering levels on DRE. Bootstrap method is also used to estimate the sampling distribution of the original sample because the data are not sampled randomly. The method is a statistical method for estimating the sampling distribution of an estimator by sampling with replacement from the original sample. The data were collected in 106 software development projects by the survey. The result of this study tells that there is some difference of DRE among the groups. The higher the software engineering level of a specific company becomes, the better its DRE gets, which means that the companies trying to improve software process can increase their good management performance.

• Journal of Korea Multimedia Society
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• v.3 no.2
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• pp.112-120
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• 2000

In this paper, we implement a real-time textile dimension inspection system. It can detect various types of real defects which determine the quality of fabric product, defect positions of textile, classify the distortion angel of moving textile and the density. In the implemented system, we measure the density of textile using zone-crossing method with optical lens to solve the noise and real-time problems. And we compensate distortion angel of textile with the classification of distortion types using gaussian gradient and mean gradient features. And also, it detecs real defects of textile and its positions using gray level co-occurrence matrix features. The implemented texile demension inspection systemcan inspect textile dimensions such as density, distortion angle, defect of textile and defect position at real-time. In the implemented proposed texitile dimension inspection system, It is possible to calculate density and detect default of textile at real-time dimension inspection system, it is possible to calculate density and detect default of textile at textile states throughout at all the significant working process such as dyeing, manufacturing, and other texitle processing.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.102-114
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• 2021

NDF (No Defect Found) is a phenomenon in which defects have been found in the manufacturing, operation and use of a product or facility, but phenomenon of defects is not reproduced in the subsequent investigation system or the cause of the defects cannot be identified. Recently, with the development of the fourth industrial revolution, convergence of hardware and software technologies in various fields is spreading to products such as aircraft, home appliances, and mobile devices, and the number of parts is increasing due to functional convergence. The application of such convergence technologies and the increase in the number of parts are major factors that lead to an increase in NDF phenomena. NDF phenomena have a significant negative impact on cost, reliability, and reliability for both manufacturers, service providers and operators. On the other hand, due to the nature of NDF phenomena such as difficult and intermittent cause identification and ambiguity in judgment, it is common to underestimate the cost of NDF or fail to take appropriate countermeasures in corporate management. Therefore, in this paper, we propose a methodology for estimating NDF costs by the PAF model which is a quality cost analysis model and ABC (Activity Based Costing) technique. The methodology of this study suggests a detailed procedure and the concept to accurately estimate the NDF costs, using ABC analysis, accounting system information, and IT system data. In addition case studies have validated the methodology. We think this could be a valid methodology to refer to when estimating the cost of other parts. And, it is meaningful to provide important judgment information in the decision-making process based on quality management and ultimately reduce NDF costs by visualizing them separately by major variable factors.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.107-116
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• 2024

Copper Filter Dryer (CFD) are responsible for removing impurities from the circulation of refrigerant in refrigeration and cooling systems to maintain clean refrigerant, and defects in CFD can lead to product defects such as leakage and reduced lifespan in refrigeration and cooling systems, making quality assurance essential. In the quality inspection stage, human inspection and defect judgment methods are traditionally used, but these methods are subjective and inaccurate. In this paper, YOLOv7 object detection algorithm was used to detect defects occurring during the CFD Shaft pipe and welding process to replace the existing quality inspection, and the detection performance of F1-Score 0.954 and 0.895 was confirmed. In addition, the cause of defects occurring during the welding process was analyzed by analyzing the sensor data corresponding to the Timestamp of the defect image. This paper proposes a method for manufacturing quality assurance and improvement by detecting defects that occur during CFD process and analyzing their causes.