NDLI: Improved method to predict cutting force in end milling considering cutting process dynamics

Content Provider	Springer Nature Link
Author	Qu, Sheng Zhao, Jibin Wang, Tianran Tian, Fengjie
Copyright Year	2015
Abstract	Accurate cutting force prediction in end milling plays an important role in studying the characteristics of milling to improve the machining quality and optimize the machining processes. To this end, a new method that improves cutting force prediction accuracy by considering cutting process dynamics and simplifies the process of computing the dynamic chip thickness is presented in this paper. The static chip thickness is calculated and the cutting process dynamics is taken into account in this method. To ensure the result accuracy and improve computing efficiency, Taylor’s series is adopted to acquire static chip thickness. Meanwhile, as feedback, the dynamic chip thickness caused by the cutter-workpiece system subjected to the cutting force is superposed on static chip thickness to get more accurate cutting force. Finally, the proposed method by dint of closed-loop system to acquire more accurate cutting force is experimentally validated in milling of plastic die steel NAK80 with a four fluted flat-end milling cutter. Cutting force coefficients and modal parameters are identified based on the experiment. Both the simulations with and without considering dynamics show good agreement with the experimental result while considering dynamics leads to closer agreement.
Starting Page	1501
Ending Page	1510
Page Count	10
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	78
Issue Number	9-12
e-ISSN	14333015
Language	English
Publisher	Springer London
Publisher Date	2015-01-11
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Milling Cutting force prediction Chip thickness Dynamics Industrial and Production Engineering Production/Logistics/Supply Chain Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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