Volume 20, Issue 9 (September 2020)                   Modares Mechanical Engineering 2020, 20(9): 2389-2401 | Back to browse issues page

XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Mehrabi Nasab M, Moetakef Imani B. Dynamic Simulation of Boring Process in B-REP Geometric Modeling Environment. Modares Mechanical Engineering 2020; 20 (9) :2389-2401
URL: http://mme.modares.ac.ir/article-15-38454-en.html
1- Mechanical Engineering Department, Engineering Faculty, Ferdowsi University of Mashhad, Mashhad, Iran
2- Mechanical Engineering Department, Engineering Faculty, Ferdowsi University of Mashhad, Mashhad, Iran , Imani@um.ac.ir
Abstract:   (1774 Views)
Prediction of the dynamic behavior of machining operations during the process is the main challenge of machining simulations. Therefore, the investigation of effective parameters in dynamic behavior is of great importance. Machining vibration is one of the most important factors. This article studied the vibration of the process by developing the dynamic model of the boring bar. The high length-to-diameter ratio of the boring tool and its flexibility cause machining vibrations. The amplitude of the tooltip vibrations is a function of the dynamic characteristic of the tool which can lead to the stability or instability of the process. Tool rigidity at low diameter to length ratios is high, and in most cutting conditions the process is stable. The impact test is used to extract the tool's dynamic parameters and dynamic modeling of the process is developed inside the environment of ACIS software which is a powerful Boundary Representation (B-rep) solid modeling engine and it is proposed a novel method for simulating the dynamic equation of boring bar by using a solid modeling technique in a precise geometric environment. The mechanistic approach is used to modeling cutting mechanistic to develop the dynamic force model in the time domain. Also, dynamic time-domain parameters such as force, acceleration, and displacement in the Simulink environment are simulated. The results confirm that the presented geometrical model by considering the tool dynamics is well capable of estimating the force signal and the chip area changes.
Full-Text [PDF 1499 kb]   (2040 Downloads)    
Article Type: Original Research | Subject: Design and manufacture by computer
Received: 2020/04/19 | Accepted: 2020/07/22 | Published: 2020/09/20

References
1. Zhao G, Cao X, Xiao W, Liu Q, Jun MBG. STEP-NC feature-oriented high-efficient CNC machining simulation. International Journal of Advanced Manufacturing Technology. 2020;106(5):2363-2375. [Link] [DOI:10.1007/s00170-019-04770-3]
2. Hendriko H. Cut geometry calculation for the semifinish five-axis milling of nonstraight staircase workpieces. Journal of Mechanical Science and Technology. 2020;34(1):1301-1311 [Link] [DOI:10.1007/s12206-020-0229-x]
3. Gao G, Baohai W, Dinghua Z, Ming L. Mechanistic identification of cutting force coefficients in bull-nose milling process. Chinese Journal of Aeronautics. 2013;26(3):823-830. [Link] [DOI:10.1016/j.cja.2013.04.007]
4. Altintas Y, Kersting P, Biermann D, Budak E, Denkena B, Lazoglu I. Virtual process systems for part machining operations. CIRP Annals. 2014;63(2):585-605. [Link] [DOI:10.1016/j.cirp.2014.05.007]
5. Sai L, Belguith R, Baili M, Dessein G, Bouzid W. An approach to modeling the chip thickness and cutter workpiece engagement region in 3 and 5 axis ball end milling. Journal of Manufacturing Processes. 2018;34:7-17. [Link] [DOI:10.1016/j.jmapro.2018.05.018]
6. Du J, Zhi H, Liu P, Bai Y. A novel method of calculating the engagement length of cutting edge in five-axis machining. The International Journal of Advanced Manufacturing Technology. 2019;102(9-12):3977-3994. [Link] [DOI:10.1007/s00170-019-03470-2]
7. Wei ZC, Guo ML, Wang MJ, Li SQ, Liu SX. Prediction of cutting force in five-axis flat-end milling. The International Journal of Advanced Manufacturing Technology. 2018;96(1-4):137-152 [Link] [DOI:10.1007/s00170-017-1380-0]
8. Wang W, Li Y, Shen W, Li X, Mou W. An industrial case study of feature-based in-process workpiece modeling. in 2012 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 14-17 October 2012, Seoul, South Korea. Piscataway: IEEE; 2012. [Link] [DOI:10.1109/ICSMC.2012.6377828]
9. Joy J, Feng HY. Frame-sliced voxel representation: An accurate and memory-efficient modeling method for workpiece geometry in machining simulation. Computer-Aided Design. 2017;88:1-13 [Link] [DOI:10.1016/j.cad.2017.03.006]
10. Gong X, Feng HY. Cutter-workpiece engagement determination for general milling using triangle mesh modeling. Journal of Computational Design and Engineering. 2016;3(2):151-160. [Link] [DOI:10.1016/j.jcde.2015.12.001]
11. Lee SW, Nestler A. Virtual workpiece: workpiece representation for material removal process. The International Journal of Advanced Manufacturing Technology. 2012;58(5-8):443-463. [Link] [DOI:10.1007/s00170-011-3431-2]
12. Inui M, Huang Y, Onozuka H, Umezu N. Geometric simulation of power skiving of internal gear using solid model with triple-dexel representation. Procedia Manufacturing. 2020;48:520-527. [Link] [DOI:10.1016/j.promfg.2020.05.078]
13. Weinert K, Du S, Damm P, Stautner M. Swept volume generation for the simulation of machining processes. International Journal of Machine Tools and Manufacture. 2004;44(6):617-628. [Link] [DOI:10.1016/j.ijmachtools.2003.12.003]
14. Spence AD, Abrari F, Elbestawi MA. Integrated solid modeller based solutions for machining. Computer-Aided Design. 2000;32(8-9):553-568. [Link] [DOI:10.1016/S0010-4485(00)00042-7]
15. Spence A, Altintas Y. A solid modeller based milling process simulation and planning system. Journal of Manufacturing Science and Engineering. 1994;116(1):61-69. [Link] [DOI:10.1115/1.2901810]
16. Moetakef-Imani B, Elbestawi M. Geometric simulation of ball-end milling operations. Journal of Manufacturing Science and Engineering. 2001;123(2):177-184. [Link] [DOI:10.1115/1.1347034]
17. Kouravand S, Moetakef-Imani B. Developing a surface roughness model for end-milling of micro-channel. Machining Science and Technology. 2014;18(2):299-321. [Link] [DOI:10.1080/10910344.2014.897846]
18. Lazoglu I, Boz Y, Erdim H. Five-axis milling mechanics for complex free form surfaces. CIRP annals. 2011;60(1):117-120. [Link] [DOI:10.1016/j.cirp.2011.03.090]
19. Boz Y, Erdim H, Lazoglu I. A comparison of solid model and three-orthogonal dexelfield methods for cutter-workpiece engagement calculations in three-and five-axis virtual milling. The International Journal of Advanced Manufacturing Technology. 2015;81(5-8):811-823. [Link] [DOI:10.1007/s00170-015-7251-7]
20. Aras E, Yip-Hoi D. Geometric modeling of cutter/workpiece engagements in three-axis milling using polyhedral representations. Journal of Computing and Information Science in Engineering. 2008;8(3):031007. [Link] [DOI:10.1115/1.2960490]
21. Altintas Y. Manufacturing automation. Cambridge: Cambridge University Press; 2012. [Link]
22. Ebrahimi M, Moetakef-Imani B. Dynamic simulation of boring process in time and frequency domain. 9th International Conference on Acoustics and Vibration (ISAV2019), 24-25 December 2019, Tehran, Iran. Tehran: Iranian Acoustics and Vibrations Association; 2019. [Link]
23. Schmitz TL, Smith KS. Machining dynamics. Berlin: Springer; 2014. [Link]

Add your comments about this article : Your username or Email:
CAPTCHA

Send email to the article author


Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.