ARTICLES

Determination of optimal geometrical parameters of peripheral mills to achieve good process stability

  • Min Wan ,
  • Heng Yuan ,
  • Ying-Chao Ma ,
  • Wei-Hong Zhang
Expand
  • 1 School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, People's Republic of China;
    2 State IJR Center of Aerospace Design and Additive Manufacturing, Northwestern Polytechnical University, Xi'an 710072, Shaanxi, People's Republic of China

Received date: 2017-09-04

  Revised date: 2018-04-26

  Online published: 2018-09-18

Supported by

This research was supported by the National Natural Science Foundation of China (Grant Nos. 51675440, 11432011 and 11620101002), the National Key Research and Development Program of China (Grant No. 3102018gxc025).

Abstract

This paper focuses on optimization of the geometrical parameters of peripheral milling tools by taking into account the dynamic effect. A substructure synthesis technique is used to calculate the frequency response function of the tool point, which is adopted to determine the stability lobe diagram. Based on the Taguchi design method, simulations are first conducted for varying combinations of tool overhang length, helix angle, and teeth number. The optimal geometrical parameters of the tool are determined through an orthogonal analysis of the maximum axial depth of cut, which is obtained from the predicted stability lobe diagram. It was found that the sequence of every factor used to determine the optimal tool geometrical parameters is the tool overhang length, teeth number, and helix angle. Finally, a series of experiments were carried out as a parameter study to determine the influence of the tool overhang length, helix angle, and teeth number on the cutting stability of a mill. The same conclusion as that obtained through the simulation was observed.

The full text can be downloaded at https://link.springer.com/content/pdf/10.1007%2Fs40436-018-0226-9.pdf

Cite this article

Min Wan , Heng Yuan , Ying-Chao Ma , Wei-Hong Zhang . Determination of optimal geometrical parameters of peripheral mills to achieve good process stability[J]. Advances in Manufacturing, 2018 , 6(3) : 259 -271 . DOI: 10.1007/s40436-018-0226-9

References

1. Altintas Y (2000) Manufacturing automation. 2nd edn. Cam bridge University Press, Cambridge
2. Wan M, Ma YC, Feng J et al (2016) Study of static and dynamic ploughing mechanisms by establishing generalized model with static milling forces. Int J Mech Sci 114:120-131
3. Yang YQ, Dai W, Liu Q (2015) Design and implementation of two-degree-of-freedom tuned mass damper in milling vibration mistigation. J Sound Vib 335:78-88
4. Wan M, Feng J, Ma YC et al (2017) Identification of milling process damping using operational modal analysis. Int J Mach Tool Manuf 122:120-131
5. Erturk A, Ozguven HN, Budak E (2006) Analytical modeling of spindle-tool dynamics on machine tools using Timoshenko beam model and receptance coupling for the prediction of tool point FRF. Int J Mach Tool Manuf 46:1901-1912
6. Zhou HM, Wang CY, Zhao ZY (2007) Dynamic characteristics of conjunction of lengthened shrink-fit holder and cutting tool in high-speed milling. J Mater Process Technol 207:154-162
7. Engin S, Altintas Y (2001) Mechanics and dynamics of general milling cutters. Part I:helical end mills. Int J Mach Tool Manuf 41:2195-2212
8. Altintas Y, Engin S, Budak E (1999) Analytical stability prediction and design of variable pitch cutters. J Manuf Sci E-T ASME 121:173-178
9. Budak E (2003) An analytical design method for milling cutters with nonconstant pitch to increase stability, part 1:theory. J Manuf Sci E-T ASME 125:29-34
10. Sellmeier V, Denkena B (2011) Stable islands in the stability chart of milling process due to unequal tooth pitch. Int J Mach Tool Manuf 51:152-164
11. Shirase K, Altintas Y (1996) Cutting force and dimensional surface error generation in peripheral milling with variable pitch helical end mills. Int J Mach Tool Manuf 36:567-584
12. Dombovari Z, Stepan G (2012) The effect of helix angle variation on milling stability. J Manuf Sci E-T ASME 134:051015
13. Subramanian M, Sakthivel M, Sooryaprakash K et al (2013) Optimization of end mill tool gerometry parameters for Al7075-T6 machining operations based on vibration amplitude by response surface methodology. Measurement 46:4005-4022
14. Li GX, Liu Q (2008) Experiment and simulation of cutter geometric parameter affecting stability in milling process. Trans Chin Soc Agric Mach 39:194-197
15. Wei ZY, Gao DQ, Mao ZY et al (2010) High-speed milling system stability study based on the cutting parameters. Modul Mach Tool Autom Manuf Tech 11:16-18
16. Neseli S, Yadiz S, Turkes E (2011) Optimizations of geometry parameters for turning operations based on the response surface methodology. Measurement 44:580-587
17. Alauddin M, El Baradie MA (1997) Tool life model for end milling steel (190 BHN). J Mater Process Technol 68:50-59
18. Zeng JW, Ren JX, Yin J et al (2013) Research on tool geometry optimization of TC18 titanium alloy milling. Avia Precis Manuf Technol 49:37-40
19. Schmitz T, Donaldson R (2000) Predicting high-speed machining dynamics by substructure analysis. CIRP Ann Manuf Technol 49:303-308
20. Wan M, Ma YC, Zhang WH et al (2015) Study on the construction mechanism of stability lobes in milling process with multiple modes. Int J Adv Manuf Technol 79:589-603
21. Insperger T, Stepan G (2002) Semi-discretization method for delayed systems. Int J Numer Methods Eng 55:503-518
22. Insperger T (2010) Full-discretization and semi-discretization for milling stability prediction:some comments. Int J Mach Tool Manuf 50:658-662
23. Zhang JZ, Chen JC, Kirby ED (2007) Surface roughness optimization in an end-milling operation using the Taguchi design method. J Mater Process Technol 184:233-239
24. Yang WH, Tarng YS (1998) Design optimization of cutting parameters for turning operations based on the Taguchi method. J Mater Process Technol 84:122-129
25. Selvaraj DP, Chandramohan P (2010) Optimization of surface roughness of AISI 304 austenitic stainless steel in dry turning operation using Taguchi design method. J Eng Sci Technol 5:293-301
26. Wan M, Dang XB, Zhang WH et al (2018) Optimization and improvement of stable processing condition by attaching additional masses for milling of thin-walled workpiece. Mech Syst Signal Process 103:196-215
27. Ahmadi K, Altintas Y (2014) Identification of machining process damping using output-only modal analysis. J Manuf Sci E-T ASME 136:051017
28. Eksioglu C, Kilic ZM, Altintas Y (2012) Discrete-time prediction of chatter stability, cutting forces, and surface location errors in flexible milling systems. J Manuf Sci E-T ASME 134:061006
Outlines

/