• Journal of Korean Society for Quality Management
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• v.46 no.4
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• pp.785-796
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• 2018

Purpose: Currently, the morale of Quality People and Quality Department in Korea is low, so it is not doing enough work. This is one of the reasons why there is no theoretical support for the role of Role of Quality People and Quality Department. In this paper propose Role of Quality People and Quality Department in Korea. Methods: We reviewed 'Quality History' of Juran and other literature Role of Quality People and future Quality. In addition, We surveyed the actual condition of Role of Quality People and Role of Quality Department in Korean. We propose Role of Quality People and Quality Department in Korea. Results: We propose the Definition, Mission, Characteristic and Quality People Knowledge for the Role of Quality People and Role of Quality Department in Korean. Conclusion: There is still work Role of Quality People and Role of Quality Department in Korean. We expect continuously to improve Quality Competitiveness by Quality Management with good Role of Quality People and Quality Department.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.610-621
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• 1998

In parameter design introduced by Taguchi, we analyze a signal-to-noise(SN) ratio. The SN ratio is a function of the expected loss due to the variation of quality characteristic. In this paper, an easy way for developing SN ratios is presented, which can be used to several quality characteristics simultaneously in parameter design. To develop such multivariate SN ratios, the transformation method of the expected loss and combining techniques are employed. And the analysis of real empirical data for an application of the proposed method is also presented.

• Journal of Korean Society for Quality Management
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• v.27 no.3
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• pp.67-78
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• 1999

In parameter design introduced by Taguchi, we analyze a performance measure, so called SN ratio. The SN ratio is a function of the expected loss due to the variation of quality characteristic. In this paper, an easy way for developing performance measures is presented, which can be used to control several quality characteristics simultaneously in parameter design. To develop such multivariate performance measures, the transformation method of the expected loss and combining techniques are employed. And the analysis of real empirical data for an application of the proposed method is also presented.

• Proceedings of the Safety Management and Science Conference
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• 2004.05a
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• pp.137-144
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• 2004

Consumers require various quality characteristics including safety. The reduction of risk concerned on product safety becomes urgent issue in leading companies. The strategy for customer satisfaction by choosing attractive quality characteristic is not enough for risk reduction in view of producer. This paper presents a method for choosing quality characteristics and risk characteristics by integrating QFD based on quality requirements and AHP based on safety requirements, also shows its application for complex equipment.

• Journal of Korean Society for Quality Management
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• v.24 no.2
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• pp.142-157
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• 1996

Robust design in industry is an approach to reducing performance variation of quality characteristic values in products and processes. In the Taguchi type robust design, the product array approach using orthogonal arrays is mainly used. However, it often requires an excessive number of experiments. In this paper, for the combined array approach to assign control and noise factors, we propose how to simultaneously optimize multiple quality characteristics. Two examples are illustrated to show the difference between the product-array approach and the combined-array approach.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.556-567
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• 1998

Robust design in industry is an approach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used the signal-to-noise ratio(SN) to achieve the appropriate set of operating conditions where variability around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for robust design to solve the dual response problems without resorting to SN. Two examples illustrate this procedure. in the two different experimental design(product array, combined array) approaches.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.10a
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• pp.244-247
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• 2001

Lubricanting characteristics in the warm forging have influence on forgeability of products. but Research on deformation characteristic of warm forging on the lubricant and lubricating method lack. This paper deform a bevel gear by warm forging and evaluate deformation loads and quality of products by each lubricants and lubricating method using oil-based lubricants(Soy, Oildag) and water-based lubricants(Deltaforge $\#31$, Renite S-26-X, Deltaglaze $\#151$). In conclusion, the less a deformation load by lubricants the more improvement a quality of product in manufacture of a bevel gear and water-based lubricants in the warm forging reduce a deformation load and improve a quality of products. Especially, Deltaforge $\31$ have excellent characteristic in the warm forging.

• Journal of the Korea Safety Management & Science
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• v.2 no.4
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• pp.139-151
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• 2000

Developing a new commercial product, it is need to connect the end users demand of quality to the industrial technology of company. For this reason, this study is to build up the users demand for the imminent marketing product of a certain company by Analytic Hierarchy Process, analyze quantitatively users subjective thoughts collected by Group Consensus, calculate the added-value of users demands and verify the consistency of users opinions by consistency-exponential-calculation. The added value obtained by this method is substituted into a user-demand item of Quality Function Deployment. And, the technical characteristic data transferred from the extracted essential factor for developing and manufacturing a new product is substituted into a technical characteristic item of QFD. The faculty of quality is firstly finished by this procedure. But, because the relation a technical characterization with users demand do not be known in new product, Wassermans method was introduced for the correlation users demand with technology and for the processing and marketing of a new product. The all assumption on this thesis was based on the reliable real data of a certain company.

• Journal of Korean Society for Quality Management
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• v.26 no.3
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• pp.60-70
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• 1998

When driving the expected loss generated by the quality deviation, Taguchi(1991b) assumed that an objective characteristic has the uniform distribution in its control limit. But it is reasonable to assume that an objective characteristic has the normal distribution than the uniform distribution. Since the triangular distribution is similar to the normal distribution and easy to handle as well, in this article, we first find the optimum measurement interval and the optimum control limit under the triangular distribution. Under the normal assumption, the modified method is compared to Taguchi's. Secondly we find the numerical value solution of the optimum measurement interval and the optimum control limit under the normal distribution.

• Journal of Korean Society for Quality Management
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• v.26 no.4
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• pp.88-100
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• 1998

Robust design in industry is an a, pp.oach to reducing performance variation of quality characteristic value in products and processes. Taguchi has used the signal-to-noise raio(SN) to achieve the a, pp.opriate set of operating conditions where variablity around target is low in the Taguchi parameter design. Taguchi has dealt with having constraints on both the mean and variability of a characteristic (the dual response problem) by combining information on both mean and variability into an SN. Many Statisticians criticize the Taguchi techniques of analysis, particularly those based on the SN. In this paper we propose a substantially simpler optimization procedure for robust design to solve the dual response problems without resorting to SN. Two examples illustrate this procedure in the two different experimental design(product array, combined array) a, pp.oaches.