- 期刊
- OpenAccess
Fuzzy and Regression Modelling of Hard Milling Process
並列摘要
The present study highlights the application of box-behnken design coupled with fuzzy and regression modeling approach for making expert system in hard milling process to improve the process performance with systematic reduction of production cost. The important input fields of work piece hardness, nose radius, feed per tooth, radial depth of cut and axial depth cut were considered. The cutting forces, work surface temperature and sound pressure level were identified as key index of machining outputs. The results indicate that the fuzzy logic and regression modeling technique can be effectively used for the prediction of desired responses with less average error variation. Predicted results were verified by experiments and shown the good potential characteristics of the developed system for automated machining environment.
延伸閱讀
- Díaz, F. V., Mammana, C. A., & Guidobono, A. P. M. (2015). Evaluation of Residual Stresses in Low, Medium and High Speed Milling. Research Journal of Applied Sciences, Engineering and Technology, 11(3), 252-258. https://www.airitilibrary.com/Article/Detail?DocID=20407467-201509-201512090024-201512090024-252-258
- Hsu, Y. Y., Liu, H. K., & Wu, B. L. (2010). On the Optimization Methods for Fully Fuzzy Regression Models. International Journal of Intelligent Technologies and Applied Statistics, 3(1), 45-55. https://doi.org/10.6148/IJITAS.2010.0301.04
- 楊承翰（2014）。Study on Parametric Optimization of Micro-Milling〔碩士論文，國立虎尾科技大學〕。華藝線上圖書館。https://doi.org/10.6827/NFU.2014.00084
- Lai, W. H. (2000). Modeling of Cutting Forces in End Milling Operations. 淡江理工學刊, 3(1), 15-22. https://doi.org/10.6180/jase.2000.3.1.02
- Lii, H. R., Tarng, Y. S., & Cheng, C. I. (1994). Modeling of Cutting Forces in Numerically Controlled End Milling Operations. 中國航空太空學會學刊, 26(3), 233-238. https://doi.org/10.6124/TAASRC.199409_26(3).06