• Corrosion Science and Technology
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• v.15 no.2
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• pp.84-91
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• 2016

The transport and deposition of corrosion products in pressurized water nuclear reactor (PWR) steam generators have led to corrosion (SCC, denting etc.) problems. Lancing, mechanical cleaning and chemical cleaning have been used to reduce these problems. The methods of lancing and mechanical cleaning have limitations in removing corrosion products due to the structure of steam generator tubes. But high temperature chemical cleaning (HTCC) with EDTA is the most effective method to remove corrosion products regardless of the structure. However, EDTA in chemical cleaning aqueous solution and chemical cleaning environments affects the integrity of materials used in steam generators. The nuclear power plants have to perform the pre-test (also called as qualification test (QT)) that confirms the effect on the integrity of materials after HTCC. This is one of the series studies that assess the effect, and this study determines the effects of 20 % EDTA aqueous solution on defective tubes in high temperature chemical cleaning environments. The depth and magnitude of defects in steam generator (SG) tubes were measured by eddy current test (ECT) signals. Surface analysis and magnitude of defects were performed by using SEM/EDS. Corrosion rate was assessed by weight loss of specimens. The ECT signals (potential and depth %) of defective tubes increased marginally. But the lengths of defects, oxides on the surface and weights of specimens did not change. The average corrosion rate of standard corrosion specimens was negligible. But the surfaces on specimens showed traces of etching. The depth of etching showed a range on the nanometer. After comprehensive evaluation of all the results, it is concluded that 20 % EDTA aqueous solution in high temperature chemical cleaning environments does not have a negative effect on defective tubes.

• Proceedings of the Safety Management and Science Conference
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• 2003.11a
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• pp.173-183
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• 2003

The articles of food is very important things to human. Since PL Law came into effect in July of the last year(2002) in Korea, many domestic firms have taken great interests in PL. And the purpose of PL Law is to provide a means for those injured by defective products to receive redress. Additionally, enterprises get to place more importance on the safety of the products, which led to improvement in competitiveness and enhancement in quality. Consequently customers can get better products. So, it aims not only to compensate the injured by defective products but also to act an incentive to maker $s^pliers of food to make their products more safe. Therefore, this study was aiming to analyze the expected risks to articles of food after the enforcement of PL Law, and to establish a defending plan.an.

• International Journal of Contents
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• v.13 no.2
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• pp.57-65
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• 2017

Recently, due to the significance of Industry 4.0, the manufacturing industry is developing globally. Conventionally, the manufacturing industry generates a large volume of data that is often related to process, line and products. In this paper, we analyzed causes of defective products in the manufacturing process using the decision tree technique, that is a well-known technique used in data mining. We used data collected from the domestic manufacturing industry that includes Manufacturing Execution System (MES), Point of Production (POP), equipment data accumulated directly in equipment, in-process/external air-conditioning sensors and static electricity. We propose to implement a model using C4.5 decision tree algorithm. Specifically, the proposed decision tree model is modeled based on components of a specific part. We propose to identify the state of products, where the defect occurred and compare it with the generated decision tree model to determine the cause of the defect.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.1
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• pp.42-51
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• 2011

Poisson model and Gamma-Poisson model are popularly used to analyze statistical behavior from defective data. The methods are based on binary criteria, that is, good or failure. However, manufacturing industries prefer polytomous criteria for classifying manufactured products due to flexibility of marketing. In this paper, I introduce two multivariate Gamma-Poisson(MGP) models and estimation methods of the parameters in the models, which are able to handle polytomous data. The models and estimators are verified on defective pixels of LCD manufacturing. Experimental results show that both the independent MGP model and the multinomial MGP model have excellent performance in terms of mean absolute deviation and the choice of method depends on the purpose of use.

• Journal of Korean Society for Quality Management
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• v.9 no.2
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• pp.10-14
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• 1981

Products are assumed to be spoiled and not recoverable when the raw material below the prescribed weight level is charged in the mold. The raw material is autoscaled and their weight is normally distributed with a given variance. This paper describes an appropriate stochastic model of determining the optimum weight allowance and the associated defective rate for auto scale system. The optimum weight allowance and the defective rate which minimizes the total loss of defective and the excess weight allowance is obtained. A numerical example for the existing rubber company is also presented and evaluated.

• Journal of the Korean Society of Safety
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• v.36 no.1
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• pp.26-35
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• 2021

Governmental bodies generally conduct investigations for product safety management once new products are released to the market, in order to prevent distribution of illegal and defective items. Further, market surveillance activities are regularly conducted by the government to ensure distribution of safe products and recall any hazardous products. The safety investigations often involve a consumer monitoring system wherein consumer organizations participate in market monitoring to conduct surveys on illegal and defective products. As a result, the monitoring results of individual consumer organizations are available separately, but an integrated analysis of the data from all consumer organizations cannot be performed, thereby deterring comprehensive evaluation of the consumer monitoring system. In this study, we analyze the individual monitoring results of consumer organizations to understand the overall status and performance of comprehensive market monitoring and present the directions for desirable market surveillance policies. To this end, the effectiveness of market surveillance related to the distribution of products is verified through analysis of the interrelationships between the monitoring processes and performances of consumer organizations as well as their impact on the performances of the monitoring implementation processes; moreover, several improvement points and direction points are presented for more desirable monitoring of the consumer markets.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.12
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• pp.38-44
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• 2019

Various automation studies have been conducted to detect defective products based on product images. In the case of machine vision-based studies, size and color error are detected through a preprocessing process. A situation may arise in which the main features are removed during the preprocessing process, thereby decreasing the accuracy. In addition, complex systems are required to detect various kinds of defects. In this study, we designed and developed a system to detect errors by analyzing various conditions of defective products. We designed the deep learning algorithm to detect the defective features from the product images during the automation process using a convolution neural network (CNN) and verified the performance by applying the algorithm to the checker-switch failure detection system. It was confirmed that all seven error characteristics were detected accurately, and it is expected that it will show excellent performance when applied to automation systems for error detection.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1565-1574
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• 2011

Scheduling of die casting is a procedure of determining quantities of cast products so as to optimize a predetermined performance criterion. This paper presents a novel scheme of preventing product shortage raised by defective castings when die casting scheduling is applied to real casting operations. The previously developed linear programming (LP) model for die casting scheduling maximizes the average efficiency of melting furnaces in regard of the usage of molten alloy. However, the LP model is not able to cope with the problem of defective products occurring in the casting process. The proposed scheme is that whenever defective products are found in a shift, the foundryman produces additional cast products using the residue of molten alloy left at the end of the next shift. Neither the calculated amount of molten alloy nor the scheduling result of the LP model does not have to be altered for this method. The simulation result demonstrates the superiority and applicability of the newly proposed scheme.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.05a
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• pp.197-200
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• 2001

In the multi-stage former, manufacture of hexagonal fitting nut was generated in a defective products about $70{\~}80\%$. Defective products reduced in a product stiffness and increased a product cost. Defects for manufacturing hexagonal fitting nut caused in a increase of ductile fracture value. So in the study, a preform designed to reduce ductile fracture value and designed preform verified through the finite element simulation. In conclusion, Ductile fracture value reduced if A round dimension of preform reduced and a part of opposition angle contributed in Plenty a volume.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.375-381
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• 1998

For products that are subject to inspections that lead to either acceptance or rejection, the p chart or control chart for proportion defective is applicable. The charting technique approach to quality control aims at alerting its user to any presentations in the properties of a manufactured product. This article presents an important tool available for quality control of a production process at the occurrence of defects in manufactured products at view low levels to improve the efficiency of the manufacturing productivity and to satisfy customer through the reduction of defect rates. To understand the consequences of the level of quality on competitive position, a more technical perspective is needed.