메뉴 건너뛰기
소속 기관 / 학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
고객센터 ENG
주제분류

논문 기본 정보

저자정보
(Inha University) (DA Consult)
저널정보
한국생산제조학회 한국생산제조학회지 한국생산제조학회지 Vol.34 No.1
오류 신고하기

피인용 0

검색

    초록·키워드

    Machine learning a artificial intelligence (AI) derives correlations between manufacturing variables from the data. These correlations can be classified into causal and noncausal relationships. In the design for manufacturing, only causal relationships are applicable because control based on causality is necessary to produce the desired product. Domain knowledge is required to confirm the causality and develop a predictive model based on causal relationships. However, domain experts often lack the AI-related knowledge necessary to develop such models, including the skills in AI, coding, and data mining. To overcome this challenge, we developed an AI system that leverages a design document interface (DDI), allowing domain experts to easily create AI models tailored to their tasks even without extensive AI expertise.

    최근 본 자료 전체보기

      UCI(KEPA) : I410-151-25-02-092303635