인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Purpose: This research aims to minimize quality deviations in computer numerical control (CNC) machining by identifying and controlling critical factors that impact quality while mitigating the
impact of noise factors.
Methods: Noise factors, such as warming-up time, bolt tightening, and cutting fluid, were analyzed using statistical techniques. The Taguchi robust design method was employed to optimize both the mean and variability in quality through signal-to-noise (S/N) ratio analysis, reducing the number of required experiments.
Results: Analysis Of Variance (ANOVA) revealed that bolt tightening is the most significant noise factor affecting quality. By considering these factors, optimal machining conditions were established, resulting in improved machining quality.
Conclusion: Controlling the three noise factors, particularly bolt tightening, and optimizing machining conditions significantly enhances CNC machining quality and consistency.
impact of noise factors.
Methods: Noise factors, such as warming-up time, bolt tightening, and cutting fluid, were analyzed using statistical techniques. The Taguchi robust design method was employed to optimize both the mean and variability in quality through signal-to-noise (S/N) ratio analysis, reducing the number of required experiments.
Results: Analysis Of Variance (ANOVA) revealed that bolt tightening is the most significant noise factor affecting quality. By considering these factors, optimal machining conditions were established, resulting in improved machining quality.
Conclusion: Controlling the three noise factors, particularly bolt tightening, and optimizing machining conditions significantly enhances CNC machining quality and consistency.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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UCI(KEPA) : I410-151-25-02-091261978
