• 디지털융복합연구
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• 제11권2호
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• pp.205-214
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• 2013

애자일 개발방법론 기반의 소프트웨어 개발 프로젝트에서도 각광받고 있는 팀의 공동작업이 일반화되고 있다. 효율적인 팀워크는 보다 효과적인 팀 관리운영과 프로젝트의 성과 측면에서 매우 중요하다. 기존의 소프트웨어 개발 인력배치는 휴리스틱 방법을 사용하였지만 이를 보완하기 위한 알고리즘적 접근법도 필요하다. 본 논문에서는 팀워크 기반의 소프트웨어 개발 프로젝트에서 개발자의 인력 배치를 위한 수학적 접근 방안을 제안하였다. 제안한 방안은 6개의 프로세스로 구성되며, 각 프로세서에서의 활동을 수학적으로 정의하였고, 기능배치매트릭스를 사용하였다. 본 논문에서 제시한 접근방법의 유용성을 증명하기 위하여 사례 연구를 제시하였다. 본 논문은 그동안 직관적이나 경험적 방법으로 팀을 구성하는 방식에서 벗어나, 계량적인 논리에 의해 인적자원을 할당하는 수학적 접근방법을 개발하였다는데 큰 의의가 있다.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2000년도 춘계 학술대회 및 국제 감성공학 심포지움 논문집 Proceeding of the 2000 Spring Conference of KOSES and International Sensibility Ergonomics Symposium
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• pp.212-217
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• 2000

The purpose of this study was to develop a design process for a functional and sensible brassiere for muddle - aged women. As a methodology, an engineering design process QFD (Quality Function Deployment) was adopted to translate the consumer's needs into product design parameters. the customer needs for the wear comfort of brassieres were extracted from a survey of 100 women aged 30 - 40. To select which items were critical and which could be traded off for other attributed or benefits. the importance ratings for the customer needs were determined. Customer needs were translated into technical language by various physical test methods and wear tests. The customer competitive assessment was generated by wear tests of 10 commercial brassieres under controlled environmental conditions of 28${\pm}$1$^{\circ}C$, 65${\pm}$3% RH. The relationship matrix between the customer needs and the means of delivering the needs was developed. Using the QFD methodology, design elements for developing a brassiere for middle-aged women could be analyzed and organized efficiently.

• 품질경영학회지
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• 제37권3호
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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.