• Journal of Applied Reliability
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• v.15 no.3
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• pp.176-180
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• 2015

A defect on the product safety display is defined by a failure to prevent the damage caused by the inappropriate explanation, direction, and caution to warn the users of the related risks. In other words, it lacks the sufficient instructions or caution for proper use and is unable to furnish the possible danger of the product and the instructions to deal with it. The defect is the responsibility of the manufacturers who are supposed to provide the adequate information so as to prevent injuries of the users. However, in order to prove the product safety display defective, there should be a comprehensive consideration in many different ways such as social norms (such as property and expectation of the product), usage form, indication of the expected risk, and awareness of consumer about the harm and possibility of avoidance of danger. The purpose of this research is to propose the content and types of standardized indication of safety in the industrial product by collecting and analyzing domestic safety information.

• Journal of the Korean Society of Safety
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• v.20 no.2 s.70
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• pp.140-145
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• 2005

The PL(Product Liability) Law has been going into effect in Korea since July 2002. Accordingly, a company's responsibility for customers who are damaged by the defect in the product safety has been gradually strict and imposed burden on management. Not only general consumers but also labors who work with machine in the field of production are included in the concept of victim of the PL Law. That is to say, when a worker is damaged by the defect of machine he can institute a PL lawsuit more aggressively, not just get the industrial accident compensation as usual, only if not his own fault but the defect of machine used in the course of production can be demonstrated. This paper intends to present suggestions to PL prevention of manufacturing companies of industrial machine through the case research of PL accidents in the area of industrial safety.

• Journal of the Korea Society of Computer and Information
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• v.23 no.2
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• pp.9-16
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• 2018

Recently, as various IP set-top boxes based on Android OS have been widely used in general households and public facilities, complaints about services and set-top boxes have continued to increase as much as other smart devices. In order to reduce this problem, the manufacturer performs the testing work before the product is commercialized. However, the testing can reduce potential defects in the product, but it can not prove that the product is free of defects. Therefore, the quality of the product can vary depending on how effective testing techniques are introduced. In this paper, we propose a new exploratory testing method that minimizes test case creation time and makes it easier to plan and execute test while simultaneously learning how to run the product under test. Using the first proposed method, the test time is reduced by about 16.7 hours and the defect detection rate is 25.4% higher than the formal specification-based testing method. Informally, the test time was shortened by about 4.7 hours and the defect detection rate was 13% higher than the informal experience-based testing method.

• Korean Journal of Materials Research
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• v.9 no.2
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• pp.139-143
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• 1999

Solidification simulation of gray cast iron sheave product was conducted with the consideration of graphite precipitation during solidification, and of casting processes such as post-inoculation method, treatment and rate, the result of which was aimed to be adopted in the field. In risering design(I), shrinkage cavities were predicted to occur in the part below the risers and center part of the product. While the former defect was considered to be due to the solidification behaviour of riser neck, the latter was due to the feeding channel. In design(II), the length of the riser neck was reduced and one top open riser was attached in the center of the product to prevent the formation of shrinkage cavities, whereby defect-free product was produced.

• Journal of the Semiconductor & Display Technology
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• v.21 no.4
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• pp.168-173
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• 2022

As the function of a product is advanced and the process is refined, the yield in the fine manufacturing process becomes an important variable that determines the cost and quality of the product. Since a fine manufacturing process generally produces a product through many steps, it is difficult to find which process or equipment has a defect, and thus it is practically difficult to ensure a high yield. This paper presents the system architecture of how to build a smart manufacturing system to analyze the big data of the manufacturing plant, and the equipment factor analysis methodology to increase the yield of products in the smart manufacturing system. In order to improve the yield of the product, it is necessary to analyze the defect factor that causes the low yield among the numerous factors of the equipment, and find and manage the equipment factor that affects the defect factor. This study analyzed the key factors of abnormal equipment that affect the yield of products in the manufacturing process using the data mining technique. Eventually, a methodology for finding key factors of abnormal equipment that directly affect the yield of products in smart manufacturing systems is presented. The methodology presented in this study was applied to the actual manufacturing plant to confirm the effect of key factors of important facilities on yield.

• Journal of Biosystems Engineering
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• v.26 no.2
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• pp.169-176
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• 2001

Defect of apple was depreciated the product value and causes storage disease seriously. To detect the defect of ‘Fuji’apple with machine vision system, the optical characteristics of defect should be investigated. In this research, absorbance spectra of defect were acquired by spectrophotometer in the range of visible and NIR region(400∼1,100nm) and L*a*b* color values were also acquired by colorimeter. NIR machine vision system was constructed with B&W camera, frame grabber, 16 tungsten-halogen lamps, variable focal length lens and NIR bandpass filter which was mounted to lens outward. Average gray values of defect at 15 NIR wavelength were acquired and the significant NIR wavelength was selected by comparing Mahalanobis distance between sound and defective apple. As the result of Mahalanobis distance analysis, the significant wavelength to discriminate the defectives in ‘Fuji’apple were found to be 720nm for scab and 970nm for bruise and cuts and 920nm was also effective regardless of defective types.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.232-235
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• 2015

Defect data contains experiential knowledge about specific work conditions. And the number of projects performed by a company is too limited for an individual to experience the various defects under the current complex construction environment. Therefore, in order to manage and prevent a reoccurrence of defects, a proper data feedback mechanism is required. However, most defect data are stored in unstructured ways, resulting in the fundamental problem of data utilization. In this paper, a new framework is proposed by using linked data technologies to improve defect data utilization. The target of this framework is to convert defect data to the ontology-based linked data format for sharing defect data from different data sources. To demonstrate it, some technical solutions are implemented by using real cases. The proposed approach can reduce data search time and improve the accuracy of search results as well. Moreover, the proposed approach can be applied to other domains that need to refer to external sources such as safety, specification, product, and regulation.

• Journal of Korean Society for Quality Management
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• v.51 no.1
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• pp.55-65
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• 2023

Purpose: The purpose of this study is to propose an optimization process to improve product yield in the process using process data. Recently, research for low-cost and high-efficiency production in the manufacturing process using machine learning or deep learning has continued. Therefore, this study derives major variables that affect product defects in the manufacturing process using eXplainable Artificial Intelligence(XAI) method. After that, the optimal range of the variables is presented to propose a methodology for improving product yield. Methods: This study is conducted using the injection molding machine AI dataset released on the Korea AI Manufacturing Platform(KAMP) organized by KAIST. Using the XAI-based SHAP method, major variables affecting product defects are extracted from each process data. XGBoost and LightGBM were used as learning algorithms, 5-6 variables are extracted as the main process variables for the injection process. Subsequently, the optimal control range of each process variable is presented using the ICE method. Finally, the product yield improvement methodology of this study is proposed through a validation process using Test Data. Results: The results of this study are as follows. In the injection process data, it was confirmed that XGBoost had an improvement defect rate of 0.21% and LightGBM had an improvement defect rate of 0.29%, which were improved by 0.79%p and 0.71%p, respectively, compared to the existing defect rate of 1.00%. Conclusion: This study is a case study. A research methodology was proposed in the injection process, and it was confirmed that the product yield was improved through verification.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.826-828
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• 2014

Recently trend of product is miniaturization. As a result, We need products surface as well as products internal defect inspection. Generally, Inspection products in production process uses a lot of optical inspection. However, This is difficult to internal inspection of products. We used optical device instead of X-ray generator. At the same time, We have developed system to determine the product defect. First, obtain X-ray image from Machine vision function. Next, Measured value is recognize suitability within error range. otherwise recognize defect. Results presence of defective products can be stored by user.

• The Korean Society of Law and Medicine
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• v.12 no.2
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• pp.65-117
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• 2011

This article analyzes the case (2008Da16776) which has the issue how patients have to prove causal relationship when patients claim against pharmaceutical companies alleging that patients were infected with virus due to contaminated blood products. The Supreme court held that: (1) if patients prove that they didn't have symptoms suggesting virus infection before administration of blood products, the virus infection had been confirmed after administration of blood products, and there were significant potential of contamination of the blood products with the virus, the defect in blood products or the negligence of pharmaceutical company in making blood products shall be presumed to cause the infection of the victim. (2) The pharmaceutical companies could reverse the presumption by proving the blood products were not contaminated, but the fact that the victims were treated with the blood products manufactured by other companies or had received blood transfusions is not enough to reverse the presumption. The case is the first decision whether the burden of proof about causal relationship could be reduced in pharmaceutical product liability lawsuit. Hereafter pharmaceutical product liability cases, it would be necessary to reduce the burden of proof about causal relationship in order to make substantive equality between patients and pharmaceutical companies.