Earticle

초록

영어

In modern manufacturing, transitioning from manual to autonomous control in CNC machining processes is crucial for improving productivity and product quality. While data-driven artificial intelligence (AI) technologies have been introduced, conventional black-box deep learning models often fail to reflect physical machining constraints, causing reliability issues on actual shop floors. This study proposes an autonomous control system for CNC machining processes integrating Asset Administration Shell (AAS)-based data standardization and an intelligent digital twin. To overcome the limitations of existing AI approaches, a physics-guided hybrid optimization model (integrating PINN-lite with 2-stage XGBoost) for deriving optimal cutting conditions and a vision AI-based predictive model for tool wear and remaining useful life (RUL) were developed. The proposed system was successfully deployed and verified in a real-world manufacturing environment. Performance evaluation certified by an authorized testing agency (KOTCA) demonstrated a 97.85% accuracy in optimal condition derivation and a 100% accuracy in tool wear prediction. The proposed closed-loop framework provides a highly reliable and practical solution for realizing level-3 autonomous factories in multi-variety, small-batch production environments.

목차

Abstract
1. 서론
2. 이론적 배경 및 관련 연구
2.1 사이버-물리 시스템(CPS)과 디지털 트윈(Digital twin)
2.2 제조 데이터 표준화 (AAS 및 OPC-UA 프로토콜)
2.3 인공지능 기반 제조 공정 최적화 기술
3. 지능형 디지털 트윈 및 자율 제어 시스템 아키텍처 설계
3.1 시스템 통합 아키텍처 개요
3.2 실시간 제조 데이터 수집 및 네트워크 인프라구축
3.3 AAS 기반 제조 데이터 모델링 및 동기화
3.4 통합 모니터링 대시보드 및 디지털 트윈 UI설계
4. 핵심 자율 제어 모델 설계 및 구현
4.1 AI 기반 절삭 가공조건 최적화 및 시뮬레이션
4.2 비전 AI 기반 칩·툴 마모 모니터링 및 품질관리
5. 시스템 적용 결과 및 성능평가
5.1. 공인기관(KOTCA) AI 모델 성능 검증
5.2 공정 혁신 개선 지표 실측 및 분석
5.3 생산성 지표(시간당 생산량) 미달에 대한 외생변수 분석
5.4. 정성적 기대효과 및 현장 수용성 분석
6. 결론
References

키워드

저자

• 김정헌 [ Jung-Heon Kim | Member, Dept. of Mechatronics, Korea Polytechnics. ]
• 노진송 [ Jin-Song Noh | Member, Chief Executive Officer , Metavu Co. ]
• 이정훈 [ Jung-Hoon Lee | Member, professor, Dept. of Control & Robotics Engineering, Gyeongsang National University ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국기계항공기술학회지(구 한국기계기술학회지) [Journal of the Korean Society of Mechanical and Aviation Technology ]

• 간기

  격월간

• pISSN

  1229-604X

• eISSN

  2508-3805

• 수록기간

  1999~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 550 DDC 620