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On Fuzzy Methods to Classify Quality Attributes in Kano Model

카노모델에서 품질요소 분류를 위한 퍼지기법 연구

  • Kim, Seong-Jun (Department of Industrial Engineering and Management Science Gangneung-Wonju National University)
  • 김성준 (강릉원주대학교 산업경영공학과)
  • Received : 2016.11.30
  • Accepted : 2016.12.15
  • Published : 2016.12.25

Abstract

The definition of quality continues to evolve. In recent years, there has been growing interest in how to satisfy customers' potential needs with an emphasis on customer-oriented quality. Two-dimensional quality proposed by Kano provides a useful framework for discovering quality attributes critical to customer satisfaction and it is widely employed for product and service development. In Kano model, quality attributes are classified into attractive, one-dimensional, must-be, indifferent, and reverse ones. Finding attractive elements among them is important for achieving customer satisfaction effectively. However, Kano's classification method has limitations in dealing with customers' ambiguous and complex ideas. The customer response itself includes uncertainty and incompleteness. To overcome this problem, fuzzy methods are incorporated with Kano's classification in this paper. According to numerical comparisons, it is shown that the fuzzy Kano method is useful for accommodating various response of customer and is helpful to identify potential needs.

품질에 대한 정의는 계속 진화하고 있다. 최근 들어서는 고객관점의 품질을 중시하며 고객의 잠재적 요구를 얼마나 잘 충족시키고 있는가에 대한 관심이 커지고 있다. 카노가 제안한 2차원적 품질의 개념은 고객만족에 중요한 품질속성을 발견하는 데 유용한 프레임워크를 제공하며 제품 및 서비스 개발을 위해 널리 적용되고 있다. 카노모델은 제품 및 서비스 품질요소를 매력적, 일원적, 필수적, 무관심, 그리고 역 품질요소로 구분한다. 그 중 매력적 요소를 발견하는 것은 고객만족의 효과적인 달성에 중요하다. 하지만 카노가 제시한 분류방법은 고객의 애매하고 복잡한 생각을 다루는 데 한계가 있다. 고객응답에는 그 자체로 불확실성과 불완전성이 포함되기 때문이다. 이를 극복하기 위해 본 논문은 퍼지기법을 이용한 품질요소 분류절차를 제시한다. 수치실험 결과, 제안된 방법은 고객의 다양한 반응을 수용하는 데 효과적이며 잠재적 요구를 식별하는 데에도 유용한 것으로 나타났다.

Keywords

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