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이상복(Sangbok Ree),이광수(Kwangsoo Lee) 한국생산관리학회 2008 韓國生産管理學會誌 Vol.19 No.4
6 시그마 기법은 기업 경쟁력 확보에 우수한 기법으로 잘 알려졌다. 6 시그마 기법의 성공 및 실패 요인에 대한 연구는 많이 진행되었다. 그러나 6 시그마를 도입한지 3년 이상 된 기업을 대상으로 한 6 시그마 성공요소에 대한 연구는 찾지 못했다. 본 연구에서는, 3년 이상 6 시그마를 도입한 기업을 대상으로 6 시그마 성공 요인을 찾는 실증적 연구이다. 연구 결과 6 시그마 추진영역, 추진방법이 추진 조직과 추진 방식보다 영향력이 큰 것을 찾았다. The Six sigma method is well known as a technique which is an excellent guarantee of company competitive power. There has been much research into the success and failure of the introduction of six sigma, but so far no research into the success of companies that have been operating six sigma for more than three years. In this study, we empirically analyze the effective factors of six sigma performance of enterprises that have been operating six sigma for more than three years. We found that propulsion area and propulsion method were more influential than propulsion organization and propulsion way. It is hoped that these results will be of practical use in the field.
이상복 ( Sangbok Ree ) 한국품질경영학회 2015 품질경영학회지 Vol.43 No.4
Purpose: This paper proposes S-NS diagram. S-NS diagram helps us find core factors which improve customer satisfaction.Methods: S-NS diagram draws a scatter diagram based on marks obtained from surveys consisting of several questions on satisfaction and non-satisfaction at the same time. S-NS diagram is divided into the 4 regions.We focused on region B which is High satisfaction and high non-satisfaction shown in S-NS diagram. Region B is the areas for needs to improve.Results: S-NS diagram can find few important factors which affect customer satisfaction. We improve Lecture Satisfaction using S-NS Diagram.Conclusion: S-NS diagram has been proven to be an effective method for improving customer satisfaction with a lecture satisfaction improvement example. We know S-NS diagram can use many fields including manufacture and service areas.
이상복(Sangbok Ree),김연수(Youn-Soo Kim),윤상운(Sangwoon Yoon) 대한산업공학회 2010 산업공학 Vol.23 No.3
Taguchi defined a good quality as ‘A correspondence of product characteristic’s expected value to the objective value satisfying the minimum variance condition.’ For his good quality, he suggested Taguchi Method which is called Robust design which is irrelevant to the effect of these noise factors. Taguchi Method which has many success examples and which is used by many manufacturing industry. But Optimal solution of Taguchi Method is one among the experiments which is not optimal area of experiment point. On the other hand, Response Surface Method (RSM) which has advantage to find optimal solution area experiments points by approximate polynomial regression. But Optimal of RSM is depended on initial point and RSM can not use many factors because of a great many experiment. In this paper, we combine the Taguchi Method and the Response Surface Method with each advantage which is called Taguchi-RSM. Taguchi-RSM has two step, first step to find first solution by Taguchi Method, second step to find optimal solution by RSM with initial point as first step solution. We give example using catapults.