• Journal of Korean Society for Quality Management
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• v.31 no.2
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• pp.194-204
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• 2003

It is very important to understand and interpret the meaning of the sigma level correctly through the Six Sigma project. Especially, the confusion over the relation between sigma level from the short-term point of view and defective proportion or DPMO from the long-term point of view may make a big gap between expected results of the Six Sigma project and real results in the field. The one-tail approximation is commonly used to calculate the sigma level both in most literatures introducing Six Sigma and actual cases of the Six Sigma project. Since the one-tail approximation undervalues the sigma level of the fields such as business and service of which the sigma level is generally low, however. there can be misleading results of the explanation of the sigma level and inappropriate project evaluation. This paper describes the relation between sigma level and defective proportion in detail and clears the difference between the one-tail and two-tail approximation.

• Journal of Korean Society for Quality Management
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• v.27 no.4
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• pp.229-240
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• 1999

Drawbacks of using sigma level as a performance metric is reviewed. The concept of sigma level is introduced and methods of calculating sigma levels for various cases are illustrated with examples. Drawbacks of using sigma level as performance metric are also discussed with some suggestions for overcoming them.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1255-1267
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• 2008

Evaluation indices for products or services are important to improve the internal process of the company and to compare those with competitive ones. The sigma level in Six Sigma management does important role to evaluate the core characteristic, CTQ(Critical To Quality), derived in the considered product/service or process. In this research, we propose an overall evaluation index for the product/service or process with multiple characteristics, in other words, multiple CTQs. The proposed overall evaluation index is useful for the cases that the single CTQ is not enough to evaluate the practical interests, for example, the final products and services with complex procedures and relatively large scaled processes. This approach is discussed with sigma level for applying Six Sigma Projects, however, it is applicable to indices based on proportion or percentage as well. The practical examples with a manufacturing process and a customer survey based on focus group interview are given for illustrations.

• Journal of Applied Reliability
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• v.1 no.1
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• pp.65-78
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• 2001

Recently, Six Sigma to increase market share , decrease costs, and grow profit margin has been adopted by some leading companies in the world. Six Sigma is expected as the optimal movement to raise the quality level remarkably and to make enterprise culture and organization based on customer and market orientation. In this paper, we study on the idea of Six Sigma, the Internal and external success case, the reliability tools using in the Six Sigma, and the difference between the existing quality movement and Six Sigma. Also, we discuss the role of reliability In Six Sigma..

• The Korean Journal of Applied Statistics
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• v.29 no.2
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• pp.369-379
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• 2016

The Sigma Level, proposed by Motorola Inc., is one of the many Process Capability Index (PCI)'s that have been presented since the 1970's. It is used to evaluate process capability and unlike other PCI's, it has an advantage in that it uses population probability distribution. However, it is originally designed for mass production and is inadequate to evaluate prototypes or early products in the R&D stages. For use in such cases, we propose an R&D target Sigma Level, derived by considering 1.5 sigma shifts in traditional sigma level from a statistical point of view. We also explain the way to find robust limits for design tolerance because the sigma level or defect probability is useful to establish economical tolerance limits at the R&D stage and mass production.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.4
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• pp.279-290
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• 2006

This paper proposes a model to assess the maturity level of Six Sigma activities. We classify the maturity level into 5 stages: initial, forming, storming, performing and mature stage. To evaluate the maturity level, 10 categories of Six Sigma with 3 factors each are identified: management leadership, belt system, expert training, establishing execution system, compensation, organization, corporate culture, customer focus, project selection, and management of project results. Scoring 277 items in total, the value of each factor is evaluated by weighted average of those items. Maturity level is appraised by rating the sum of scores of 10 categories that are obtained by summing up the values of its 3 factors. Values of weights and criteria of rating maturity levels are determined by analyzing 90 companies and Six Sigma exper's opinion. This study also shows the actual appraisal results of some companies.

• Journal of Korean Society for Quality Management
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• v.37 no.3
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• pp.74-82
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• 2009

This article presents a six sigma project for improving purchase conversion rate in mobile game site. The project was carried out based on DMAIC process. First, a defect rate is defined as low purchase conversion rate. In addition, 60-days purchase data was analyzed and it is shown that the defects level was 2.48 sigma level. In this study, in order to raise the sigma level, six personalization services were used in the mobile game site. Six factors were determined based on FDPM(Functional Deployment Process Map), fishbone chart, linear regression analysis, effort-performance matrix, and so on. The sigma level of defects has improved from 2.48 to 2.93.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.1
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• pp.31-40
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• 2022

Six Sigma is a philosophy and systematic methodology for quality improvement. It encourages continuous quality improvement efforts to achieve the ideal goal of 6σ. Sigma(σ) is a statistic representing the standard deviation of the normal distribution, and 6σ level means a level where the tolerance of the specification is six times the standard deviation of the process distribution. In terms of the defective rate, the 6σ level achieves the 0.002 defectives per one million units. However, in the field, the 6σ level is used in the sense of achieving 3.4 defects per one million opportunities, which shows a large gap from the 6σ level in the statistical viewpoint. This is because field practitioners accept a 1.5σ shift of the mean of process when calculating the defective rate under sigma level. It said that the acceptance of 1.5σ shift of the mean is from experience, but there is no research or theoretical explanation to support it logically. Although it is a non-scientific explanation based on experience, considering that there has been no objection to the 1.5σ shift for a long time and it is rather accepted, it is judged that there is a reasonable basis for the 1.5σ shift. Therefore, this study tries to find a reasonable explanation through detective power of control chart via the run-rules to the 1.5σ shift empirically recognized by practitioners.

• Proceedings of the Korean Reliability Society Conference
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• 2005.06a
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• pp.141-145
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• 2005

Nowadays, most industries take $B_{6\sigma}$ quality level as a goal of the ultimate quality level of their products. On the other hand, $B_{10}$ to life indicates the time that $10\%$ of products are failed. There is no relation between the $B_{6\sigma}$ quality level and the $B_{10}$ to life. Therefore, some industries perform their quality control activities and reliability engineering activities separately. So I propose one measure which can express quality and reliability level simultaneously for the products to pursue quality and reliability activities together in the industry.

• Industrial Engineering and Management Systems
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• v.10 no.3
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• pp.232-237
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• 2011

Design for Six Sigma (DFSS) has been implemented in many companies to enhance their business performance and customer satisfaction. However, DFSS has not been widely applied to the aircraft industry which operates large, complex development programs. In this paper, the characteristics of an aeronautical product development program are analyzed to figure out the limitations of current DFSS methodology and the prerequisite to deployment of DFSS at the program level is suggested.