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.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2024.12
- 수록면
- 346 - 353 (8page)
- DOI
- 10.33162/JAR.2024.12.24.4.346
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초록· 키워드
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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.
목차
1. Introduction
2. Motivating Example
3. Experiment of Design (DOE) using taguchi method
4. Validation results
5. Conclusion
References
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