설계 문서 접점을 이용한 개선 업무용 사용자 수정형 AI 인과 예측 모델 개발

User-Modified Artificial Intelligence Causal Prediction Model for Process Improvement Using Design Document Interface
  • 이창선
  • 이상철

초록

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.

키워드

User-modified AIMG AI(model generation AI)DDI(design document interface)Understandable and modifiable AIAI chef
제목
설계 문서 접점을 이용한 개선 업무용 사용자 수정형 AI 인과 예측 모델 개발
제목 (타언어)
User-Modified Artificial Intelligence Causal Prediction Model for Process Improvement Using Design Document Interface
저자
이창선이상철
발행일
2025-02
유형
Y
저널명
한국생산제조학회지
34
1
페이지
64 ~ 71