한국전자통신학회논문지 (The Journal of the Korea institute of electronic communication sciences)

한국전자통신학회 (Korea Institute of Electronic Communication Science)
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AI 기반의 주조 공정 파라미터 최적화를 통한 알고리즘 개선

Algorithm Improvement Through AI-Based Casting Process Parameter Optimization

  • 투고 : 2023.05.02
  • 심사 : 2023.06.17
  • 발행 : 2023.06.30
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초록

제조 공정 데이터에 있어 주조 공정은 가장 중요한 공정이면서 높은 불량률의 원인을 발생시키는 공정이다. 주조 공정의 품질관리는 생산성과 품질평가의 핵심 요소라 할 수 있다. 본 연구에서는 공정 데이터를 통한 요인 분석, 상관 분석, 회귀 분석 결과를 기반으로 최적화 된 머신러닝 모델 알고리즘을 개발한다. 이를 적용한 주조공정을 통해서 불량률을 줄이고 스마트 팩토리의 데이터 적합성을 검증하고자 한다.

The quality of the casting process generates the largest source of defects in the manufacturing process, so its management is a key factor in productivity and quality evaluation. Based on the results of factor analysis, correlation analysis, and regression analysis with process data, this study aims to optimize the machine learning model to reduce the defect rate and verify the data suitability for smart factories.

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과제정보

이 논문은 2023년 순천대학교 교연비 사업에 의하여 연구되었음.

참고문헌

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