Browse > Article
http://dx.doi.org/10.7735/ksmte.2013.22.2.292

A Concept of Self-Optimizing Forming System  

Park, Hong-Seok (울산대학교 기계공학부)
Hoang, Van-Vinh (울산대 기계공학부)
Song, Jun-Yeob (한국기계연구원)
Kim, Dong-Hoon (한국기계연구원)
Le, Ngoc-Tran (울산대 기계공학부)
Publication Information
Journal of the Korean Society of Manufacturing Technology Engineers / v.22, no.2, 2013 , pp. 292-297 More about this Journal
Abstract
Nowadays, a strategy of the self-optimizing machining process is an imperative approach to improve the product quality and increase productivity of manufacturing systems. This paper presents a concept of self-optimizing forming system that allows the forming system automatically to adjust the forming parameters online for guarantee the product quality and avoiding the machine stop. An intelligent monitoring system that has the functions of observation, evaluation and diagnostic is developed to evaluate the pully quality during forming process. Any abnormal variation of forming machining parameters could be detected and adjusted by an intelligent control system aiming to maintain the machining stability and the desired product quality. This approach is being practiced on the pully forming machine for evaluating the efficiency of the proposed strategy.
Keywords
Self-optimizing; Forming process; Online monitoring; Intelligent control; Fuzzy Logic;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Wu, C. L., Haboush, R. K., 1990, Artificial intelligence for adaptive machining control of surface finish, US Patent: 4926309.
2 Patel, S., Wirral (GB), 2004, Method for optimizing formulations, US Patent: 6757667.
3 Colding, B., Novak, A., Sandstrom, U., Jakobsson, G., 1977, Adaptive control of cutting machining operations, US Patent: 4031368.
4 Sadler, J. P., Jawahir, I. S., Zhongjie Da, Seog S. Lee, 1999, Optimization of machining with progressively worn cutting tool, US Patent: 5903474,
5 Abellan, J. V., Romero, F., Siller, H. R., Estruch, A., Vila, C., 2008, Adaptive control optimization of cutting parameters for high quality machining operations based on neural networks and search algorithm, I-Tech, Vienna, Austria, pp. 472.
6 Chien, W. T., Chou, C. Y., 2001, "The predictive model for machinability of 304 stainless steel," Journal of Materials Processing Technology, Vol. 118, No. 1-3, pp. 442-447.   DOI   ScienceOn
7 Stella, H., Alena, V., 2012, "Application of Fuzzy Principles in Evaluating Quality of Manufacturing Process," Word Scientific and Engineering Academy and Society, Vol. 7, No. 2, pp. 50-59.
8 Cus, F., Zuperl, U., 2006, "Approach to optimization of cutting conditions by using artificial neural networks," Journal of Materials Processing Technology, Vol. 173, No. 3, pp. 281-290.   DOI   ScienceOn
9 Liu, Y., Zuo, L., Cheng, T., 2000, "A neural network based fuzzy learning controller and its experimental application to milling," International Journal of Computer Integrated Manufacturing, Vol. 13, No. 5, pp. 461-466.   DOI   ScienceOn
10 Xi, J., Liao, G., 2009, "Cutting parameter optimization based on particle swarm optimization," International Conference on Intelligent Computation Technology and Automation, Vol. 01, pp. 255-258.
11 Cruz, E. D., Aguiar, P. R., Machado, A. R., Bianchi, E. C., 2012, "Monitoring in precision metal drilling process using multi-sensors and neural network," The International Journal of Advanced Manufacturing Technology, Vol. 66, No. 1-4, pp. 151-158.
12 Cus, F., Zuperl, U., Kiker, E., Milfelner, M., 2008, "Adaptive self-learning controller design for federate maximization of machining process," Journal of Achivements in Materials and Manufacturing, Vol.31, No. 2, pp. 469-476.
13 Cus, F., Zuperl, U., Kiker, E., MIIfelner, M., 2006, "Adaptive controller design for feedrate maximization of machining process," Journal of Achievements in Materials and Manufacturing Engineering, Vol. 17, No. 1-2, pp.237-240.
14 Chen, M. D., Hsu, R. Q., Fuh, K. H., 2005, "An analysis of force distribution in shear spinning of cone," International Journal of Mechanical Sciences, Vol. 47, No. 6, pp. 902-921.   DOI   ScienceOn
15 Yau, H. T., 2006, "Nonlinear rule-based controller for chaos synchronization of two gyros with linear-pluscubic damping," Chaos - Solitons and Fractals, Vol. 34, No. 4, pp. 1357-1365.
16 Kratmüller, M., 2009, "The Adaptive Control of Nonlinear Systems Using the T-S-K Fuzzy Logic," Acta Polytechnica Hungarica, Vol. 6, No. 2, pp. 5-16.
17 Quigley, E., Monaghan, J., 2000, "Metal forming: an analysis of spinning processes," Journal of Materials Processing Technology, Vol. 103, No. 1, pp.114-119.   DOI   ScienceOn
18 Klocke, F., Sheet Metal Forming I, Lecture 3, Fraunhofer IPT.
19 Prasopchaichana, K., Kwon, O. Y., 2008, "Sensor Fusion and Neural Network Analysis for Drill-Wear Monitoring," Transactions of the Korean Society of Machine Tool Engineers, Vol. 17, No. 1, pp. 77-85.   과학기술학회마을