Journal of Intelligence and Information Systems (지능정보연구)

Korea Intelligent Information System Society (한국지능정보시스템학회)
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A Study on the Development Methodology of Intelligent Medical Devices Utilizing KANO-QFD Model

지능형 메디컬 기기 개발을 위한 KANO-QFD 모델 제안: AI 기반 탈모관리 기기 중심으로

  • Kim, Yechan (School of Management and Economics, Handong Global University) ;
  • Choi, Kwangeun (School of Management and Economics, Handong Global University) ;
  • Chung, Doohee (School of Global Entrepreneurship and ICT, Handong Global University)
  • 김예찬 (한동대학교 경영경제학부) ;
  • 최광은 (한동대학교 경영경제학부) ;
  • 정두희 (한동대학교 ICT창업학부)
  • Received : 2021.12.01
  • Accepted : 2022.01.03
  • Published : 2022.03.31
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Abstract

With the launch of Artificial Intelligence(AI)-based intelligent products on the market, innovative changes are taking place not only in business but also in consumers' daily lives. Intelligent products have the potential to realize technology differentiation and increase market competitiveness through advanced functions of artificial intelligence. However, there is no new product development methodology that can sufficiently reflect the characteristics of artificial intelligence for the purpose of developing intelligent products with high market acceptance. This study proposes a KANO-QFD integrated model as a methodology for intelligent product development. As a specific example of the empirical analysis, the types of consumer requirements for hair loss prediction and treatment device were classified, and the relative importance and priority of engineering characteristics were derived to suggest the direction of intelligent medical product development. As a result of a survey of 130 consumers, accurate prediction of future hair loss progress, future hair loss and improved future after treatment realized and viewed on a smartphone, sophisticated design, and treatment using laser and LED combined light energy were realized as attractive quality factors among the KANO categories. As a result of the analysis based on House of Quality of QFD, learning data for hair loss diagnosis and prediction, micro camera resolution for scalp scan, hair loss type classification model, customized personal account management, and hair loss progress diagnosis model were derived. This study is significant in that it presented directions for the development of artificial intelligence-based intelligent medical product that were not previously preceded.

AI 기술이 결합된 지능형 제품은 기술적 차별화를 실현하며 시장 경쟁력을 높일 수 있는 잠재성을 지닌다. 하지만 시장 수용도를 극대화 할 수 있는 AI 기반의 신제품 개발 방법론은 부재하다. 본 연구는 AI 기반의 지능형 제품 개발에 대한 방법론으로서 KANO-QFD 통합 모델을 제안한다. 실증적인 분석을 위한 구체적 사례로 탈모 예측 및 치료 기기에 대한 소비자 요구조건(Customer Requirements)의 유형을 분류하고, 이를 구현하기 위한 기술적 요구사항(Engineering Characteristics)의 상대적 중요도 및 우선순위를 도출하여 지능형 메디컬 신제품 개발의 방향을 제시하였다. 소비자 130명을 대상으로 실시한 설문조사 분석 결과, KANO 카테고리 중 매력적 품질(Attractive Quality) 요소로 미래 탈모 진행 상황에 대한 정확한 예측, 미래 탈모 모습 및 치료 후 개선된 미래 모습을 실물화하여 스마트폰으로 보고, 세련된 디자인, 레이저와 LED 빛 복합 에너지를 이용한 치료 등이 도출되었다. QFD의 품질의 집(House of Quality)을 기반으로 분석한 결과, 탈모 진단 및 예측을 위한 학습 데이터, 두피 스캔용 Micro 카메라 해상도, 탈모 유형 분류 모델, 맞춤화를 위한 개인별 계정 관리, 탈모 진행상황 진단 모델 순으로 상대적 중요도 및 우선순위가 도출되었다. 본 연구는 기존에 선행되지 않았던 AI 기반의 지능형 메디컬 제품 개발에 대한 방향을 제시하였다는 면에서 의의를 지닌다.

Keywords

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