Browse > Article

A Study on feedrate Optimization System for Cutting Force Regulation  

김성진 (통일중공업)
정영훈 (포항공과대학교 기계공학과 대학원)
조동우 (포항공과대학교 기계공학과)
Publication Information
Abstract
Studies on the optimization of machining process can be divided into two different approaches: off-line feedrate scheduling and adaptive control. Each approach possesses its respective strong and weak points compared to each other. That is, each system can be complementary to the other. In this regard, a combined system, which is a feedrate control system fur cutting force optimization, was proposed in this paper to make the best of each approach. Experimental results show that the proposed system could overcome the weak points of the off-line feedrate scheduling system and the adaptive control system. In addition, from the figure, it can be confirmed that the off-line feedrate scheduling technique can improve the machining quality and can fulfill its function in the machine tool which has a adaptive controller.
Keywords
Cutting Force; Adaptive Control; Feedrate Scheduling; Optimized NC Code; Fuzzy;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Hsu, P. L. and Fann, W. R., 'Fuzzy Adaptive Control of Machining Processes with a Self-Learning Algorithm,' Trans. of the ASME Journal of Manufacturing Science and Engineering, Vol. 118, pp. 522-530, Nov. 1996   DOI   ScienceOn
2 Altintas, Y. and Spence, A. D., 'End Milling Force Algorithms for CAD Systems,' Annals of the CIRP, Vol. 40, No.1, pp. 31-34, 1991   DOI   ScienceOn
3 http://www.cgtech.com/
4 Yun, W. S. and Cho, D. W., 'Accurate 3D Cutting Force Prediction Using Cutting Condition Independent Coefficients in End Milling,' Int. J. of Machine Tools and manufacture, Vol. 41, Issue 4, pp. 463-478, 2001   DOI   ScienceOn
5 Tarng, Y. S. and Cheng, S. T., 'Fuzzy Control of Feed Rate in End Milling Operations,' International Journal of Machine Tools and Manufacture, Vol. 33, No.4, pp. 643-650, 1993   DOI   ScienceOn
6 Y. Altintas, 'Prediction of Cutting Forces and Tool Breakage in Milling from Feed Drive Current Measurements,' Trans. of the ASME Journal of Engineering for Industry, Vol. 114, pp. 386-392, Nov. 1992   DOI
7 http://www.lem.com/
8 윤원수, 고정훈, 조동우, '가상공작기계의 연구개발 Part I, Part II,' 한국정밀공학회지, 제 18 권 제 11 호,pp. 74-85, 2001   과학기술학회마을
9 이한울, 고정훈, 조동우, '향상된 절삭력 모델 기반의 NC 코드 최적화,' 한국정밀공학회 2001년도 추계학술대회 논문집, pp. 37-42, 2001   과학기술학회마을
10 김태용, 최덕기, 주종남, 김종원, '송모터 전류 감시를 통한 절삭력의 간접측정과 절삭공정 감시 및 제어에의 응용,' 한국정밀 공학회지, Vol. 13, No.2, pp. 133-145, 1996
11 Tarng, Y. S. and Cheng, S. T., 'Fuzzy Control of Feed Rate in End Milling Operations,' International Journal of Machine Tools and Manufacture, Vol. 33, No.4, pp. 643-650, 1993   DOI   ScienceOn
12 Hsu, P. L. and Fann, W. R., 'Fuzzy Adaptive Control of Machining Processes with a Self-Learning Algorithm,' Trans. of the ASME Journal of Manufacturing Science and Engineering, Vol. 118, pp. 522-530, Nov. 1996   DOI   ScienceOn
13 Kline, W. A., DeVor, R. E. and Lindberg, R., 'The Prediction of Cutting Forces in End Milling with Application to Cornering Cuts,' Int. J. Mach. Tool Des. Res., Vol. 22, No.1, pp. 7-21,1982   DOI
14 Takata, S. 'Generation of Machining Scenario and Its Applications to Intelligent Machining Operations, ' Annals of CIRP Vol. 42/1, pp. 531-534,1993   DOI   ScienceOn