• 품질경영학회지
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• 제44권2호
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• pp.341-356
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• 2016

Purpose: The purpose of this paper is to study whether the adoption of Six Sigma quality management by a firm positively affects its financial performance. The correlation between the duration of Six Sigma implementation period and the financial status of the firm is investigated as well. Methods: We conduct the analysis using data from Manufacturing Industry Productivity Panel Survey 2013 provided by Korea Productivity Center and Ministry of Trade, Industry and Energy. Propensity score matching is used to reduce sample selection bias of observational study. Furthermore, we use multiple linear regression in order to study the relationship between the implementation of Six Sigma quality management and financial performance. The return on assets and ratio of net income to net sales are considered as dependent variable and implementation of Six Sigma as independent variable. Results: The indication of this analysis is that implementation of Six Sigma quality management does not significantly enhance financial status. The firms that adopted Six Sigma quality management were categorized into three groups according to the implementation period. Comparison of each group with the firms that do not adopt Six Sigma quality management does not show statistically significant enhancement of financial status. Conclusion: In conclusion, both adoption and duration of six sigma quality management do not affect financial performance significantly.

• 한국융합학회논문지
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• 제10권11호
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• pp.149-159
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• 2019

식스시그마는 시장과 고객의 패러다임과 트렌드의 변화에 맞추어 모든 사업의 프로세스와 전략을 개선하는 경영 혁신운동이다. 식스시그마 프로젝트 선정에 관한 기존의 연구는 있으나 불완전한 정보환경 하에서 프로젝트 선정을 위한 연구는 거의 없다. 본 연구의 목적은 불완전한 정보 하에서 올바른 프로젝트 선정을 위해 통합 MCDM 기법을 적용 방법을 제안하는 것이다. 식스시그마 프로젝트 선정을 위해 4단계인 1) 평가기준 간 가중치 결정 2) 팀 멤버 간 전문역량의 상대적 중요도 결정 3) 프로젝트 선호도 척도 산정 4) 최종 프로젝트 우선순위 결정 등을 위해 그룹 Fuzzy AHP, 불완전한 정보환경 하에서의 비퍼지화 TrFN 변환, GRA의 통합기법을 제안하였다. 본 연구에서 제안한 식스시그마 프로젝트 선정단계의 적용방안에 대한 이해를 돕기 위해 수치예가 제시되었다.

• 산업경영시스템학회지
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• 제45권1호
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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.