A review of cutting chatter suppression methods

doi:10.1007/s40436-025-00557-w

Abstract

Abstract: Cutting chatter is a major factor that limits machining efficiency and can negatively impact the quality of a cutting surface. Chatter suppression is crucial for improving machining efficiency and maximizing business benefits. However, most chatter suppression techniques are difficult to use on a massive scale in actual production because of their high cost and limited applicability. In the investigation of chatter suppression, particularly in recent years, unique and effective suppression methods have been developed that must be summarized and arranged, and their advantages and disadvantages must be evaluated in depth. Therefore, this paper summarizes and systematically discusses recent research advancements in chatter suppression methods. Furthermore, future research directions for chatter suppression technologies are predicted.

The full text can be downloaded at https://doi.org/10.1007/s40436-025-00557-w

Key words: Regenerative chatter, Stability lobe diagram (SLD), Cutting process, Suppression method

Hai-Yong Sun, Hong-Yu Jin, Jian-Xin Song, Zhen-Yu Han, Hong-Ya Fu. A review of cutting chatter suppression methods[J]. Advances in Manufacturing, 2026, 14(1): 211-243.

TrendMD

References

[1] Yue C, Gao H, Liu X et al (2019) A review of chatter vibration research in milling. Chin J Aeronaut 32(2):215-242
[2] Munoa J, Beudaert X, Dombovari Z et al (2016) Chatter suppression techniques in metal cutting. CIRP Ann 65(2):785-808
[3] Zhu L, Liu C (2020) Recent progress of chatter prediction, detection and suppression in milling. Mech Syst Signal Process 143:106840. https://doi.org/10.1016/j.ymssp.2020.106840
[4] Dong X, Shen X, Fu Z (2021) Stability analysis in turning with a variable spindle speed based on the reconstructed semi-discretization method. Int J Adv Manuf Technol 117(11):3393-3403
[5] Zhang X, Wang C, Liu J et al (2019) Robust active control based milling chatter suppression with perturbation model via piezoelectric stack actuators. Mech Syst Signal Process 120:808-835
[6] Quintana G, Ciurana J (2011) Chatter in machining processes: a review. Int J Mach Tool Manuf 51(5):363-376
[7] Yang Y, Zhang WH, Ma YC et al (2016) Chatter prediction for the peripheral milling of thin-walled workpieces with curved surfaces. Int J Mach Tool Manuf 109:36-48
[8] Yang Y, Zhang WH, Ma YC et al (2019) An efficient decomposition-condensation method for chatter prediction in milling large-scale thin-walled structures. Mech Syst Signal Process 121:58-76
[9] Liu YP, Kilic ZM, Altintas Y (2022) Monitoring of in-process force coefficients and tool wear. CIRP J Manuf Sci Technol 38:105-119
[10] Jiang S, Zhan D, Liu Y et al (2022) Modeling of variable-pitch/helix milling system considering axially varying dynamics with cutter runout offset and tilt effects. Mech Syst Signal Process 168:108674. https://doi.org/10.1016/j.ymssp.2021.108674
[11] Liu X, Gao H, Yue C et al (2018) Investigation of the milling stability based on modified variable cutting force coefficients. Int J Adv Manuf Technol 96(9):2991-3002
[12] Chen X, Zhang Z, Wang Q et al (2022) A new method for prediction of cutting force considering the influence of machine tool system and tool wear. Int J Adv Manuf Technol 120(3):1843-1852
[13] Shi KN, Liu N, Liu CL et al (2022) Indirect approach for predicting cutting force coefficients and power consumption in milling process. Adv Manuf 10(1):101-113
[14] Yu G, Wang L, Wu J (2018) Prediction of chatter considering the effect of axial cutting depth on cutting force coefficients in end milling. Int J Adv Manuf Technol 96(9):3345-3354
[15] Wang G, Peng D, Qin X et al (2012) An improved dynamic milling force coefficients identification method considering edge force. J Mech Sci Technol 26(5):1585-1590
[16] Ozturk E, Ozkirimli O, Gibbons T et al (2016) Prediction of effect of helix angle on cutting force coefficients for design of new tools. CIRP Ann 65(1):125-128
[17] Zhuo Y, Han Z, Duan J et al (2021) Estimation of vibration stability in milling of thin-walled parts using operational modal analysis. Int J Adv Manuf Technol 115(4):1259-1275
[18] Schmitz TL, Donalson R (2000) Predicting high-speed machining dynamics by substructure analysis. CIRP Ann 49(1):303-308
[19] Albertelli P, Goletti M, Monno M (2013) A new receptance coupling substructure analysis methodology to improve chatter free cutting conditions prediction. Int J Mach Tool Manuf 72:16-24
[20] Ji Y, Bi Q, Zhang S et al (2018) A new receptance coupling substructure analysis methodology to predict tool tip dynamics. Int J Mach Tool Manuf 126:18-26
[21] Yang Y, Wan M, Ma YC et al (2018) A new method using double distributed joint interface model for three-dimensional dynamics prediction of spindle-holder-tool system. Int J Adv Manuf Technol 95(5):2729-2745
[22] Postel M, Bugdayci B, Wegener K (2020) Ensemble transfer learning for refining stability predictions in milling using experimental stability states. Int J Adv Manuf Technol 107(9):4123-4139
[23] Schmitz T, Cornelius A, Karandikar J et al (2022) Receptance coupling substructure analysis and chatter frequency-informed machine learning for milling stability. CIRP Ann 71(1):361-364
[24] Stepan G, Kiss AK, Ghalamchi B et al (2017) Chatter avoidance in cutting highly flexible workpieces. CIRP Ann 66(1):377-380
[25] Wang X, Song Q, Liu Z (2021) Dynamic model and stability prediction of thin-walled component milling with multi-modes coupling effect. J Mater Process Technol 288:116869. https://doi.org/10.1016/j.jmatprotec.2020.116869
[26] Eynian M (2019) In-process identification of modal parameters using dimensionless relationships in milling chatter. Int J Mach Tool Manuf 143:49-62
[27] Dang XB, Wan M, Yang Y et al (2019) Efficient prediction of varying dynamic characteristics in thin-wall milling using freedom and mode reduction methods. Int J Mech Sci 150:202-216
[28] Zhenmin LI, Song Q, Jin P et al (2023) Chatter suppression techniques in milling processes: a state of the art review. Chin J Aeronaut 37(7):1-23
[29] Otto A, Khasawneh FA, Radons G (2015) Position-dependent stability analysis of turning with tool and workpiece compliance. Int J Adv Manuf Technol 79:1453-1463
[30] Tian L, Wu J, Xiong Z et al (2015) Active chatter suppression in turning of low-rigidity workpiece by system matching. In: Proceedings of the 8th international conference on intelligent robotics and applications, ICIRA 2015, Springer. https://doi.org/10.1007/978-3-319-22876-1_53
[31] Lu K, Gu F, Longstaff A et al (2020) An investigation into tool dynamics adaptation for chatter stability enhancement in the turning of flexible workpieces. Int J Adv Manuf Technol 111:3259-3271
[32] Sun Y, Jiang S (2018) Predictive modeling of chatter stability considering force-induced deformation effect in milling thin-walled parts. Int J Mach Tool Manuf 135:38-52
[33] Li W, Wang L, Yu G (2022) Chatter prediction in flank milling of thin-walled parts considering force-induced deformation. Mech Syst Signal Process 165:108314. https://doi.org/10.1016/j.ymssp.2021.108314
[34] Li X, Zhao W, Li L et al (2015) Modeling and application of process damping in milling of thin-walled workpiece made of titanium alloy. Shock Vib 2015:431476. https://doi.org/10.1155/2015/431476
[35] Yue C, Gao H, Liu X et al (2018) Analytical prediction of part dynamics and process damping for machining stability analysis. Procedia CIRP 72:1463-1468
[36] Tunc LT, Budak E (2012) Effect of cutting conditions and tool geometry on process damping in machining. Int J Mach Tool Manuf 57:10-19
[37] Feng J, Wan M, Gao TQ et al (2018) Mechanism of process damping in milling of thin-walled workpiece. Int J Mach Tool Manuf 134:1-19
[38] Wang D, Loser M, Ihlenfeldt S et al (2019) Milling stability analysis with considering process damping and mode shapes of in-process thin-walled workpiece. Int J Mech Sci 159:382-397
[39] Feng J, Wan M, Dong ZY et al (2019) A unified process damping model considering the varying stiffness of the milling system. Int J Mach Tool Manuf 147:103470. https://doi.org/10.1016/j.ijmachtools.2019.103470
[40] Tuysuz O, Altintas Y (2019) Analytical modeling of process damping in machining. J Manuf Sci Eng 141(6):061006. https://doi.org/10.1115/1.4043310
[41] Tang X, Peng F, Yan R et al (2021) Nonlinear process damping identification using finite amplitude stability and the influence analysis on five-axis milling stability. Int J Mech Sci 190:106008. https://doi.org/10.1016/j.ijmecsci.2020.106008
[42] Wan M, Li Y, Wen DY et al (2022) On cutting process damping for small cutters by including the influences of the dead metal zone and elastic recovery. J Mater Process Technol 306:117608. https://doi.org/10.1016/j.jmatprotec.2022.117608
[43] Altintas Y, Budak E (1995) Analytical prediction of stability lobes in milling. CIRP Ann 44(1):357-362
[44] Altintas Y, Stepan G, Merdol D et al (2008) Chatter stability of milling in frequency and discrete time domain. CIRP J Manuf Sci Technol 1(1):35-44
[45] Ding Y, Zhu L, Zhang X et al (2010) A full-discretization method for prediction of milling stability. Int J Mach Tool Manuf 50(5):502-509
[46] Xia Y, Wan Y, Luo X et al (2021) Milling stability prediction based on the hybrid interpolation scheme of the newton and lagrange polynomials. Int J Adv Manuf Technol 112(5):1501-1512
[47] Xia Y, Wan Y, Luo X et al (2021) An improved numerical integration method to predict the milling stability based on the lagrange interpolation scheme. Int J Adv Manuf Technol 116(7):2111-2123
[48] Xia Y, Wan Y, Du J et al (2022) Fast prediction of chatter stability in milling process based on an updated numerical solution scheme. Int J Adv Manuf Technol 123:4041-4050
[49] Takuya K, Suzuki N, Hino R et al (2013) A novel design method of variable helix cutters to attain robust regeneration suppression. Procedia CIRP 8:363-367
[50] Hamann D, Walz NP, Fischer A et al (2018) Fuzzy arithmetical stability analysis of uncertain machining systems. Mech Syst Signal Process 98:534-547
[51] Totis G (2009) RCPM—a new method for robust chatter prediction in milling. Int J Mach Tool Manuf 49(3/4):273-284
[52] Hajdu D, Insperger T, Bachrathy D et al (2017) Prediction of robust stability boundaries for milling operations with extended multi-frequency solution and structured singular values. J Manuf Process 30:281-289
[53] Totis G, Sortino M (2020) Polynomial chaos-kriging approaches for an efficient probabilistic chatter prediction in milling. Int J Mach Tool Manuf 157:103610. https://doi.org/10.1016/j.ijmachtools.2020.103610
[54] Gupta P, Singh B (2022) Ensembled local mean decomposition and genetic algorithm approach to investigate tool chatter features at higher metal removal rate. J Vib Control 28(1/2):30-44
[55] Mishra R, Gupta P, Singh B (2023) An intelligent approach to extract chatter and metal removal rate features impromptu from milling sound signal. Proc Inst Mech Eng Part E J Process Mech Eng 238(5):2235-2245
[56] Mishra R, Singh B (2023) SBLMD-ANN-MOPSO-based hybrid approach for determining optimum parameter in CNC milling. Soft Comput 27(11):7299-7320
[57] Bediaga I, Munoa J, Hernandez J et al (2009) An automatic spindle speed selection strategy to obtain stability in high-speed milling. Int J Mach Tool Manuf 49(5):384-394
[58] Seguy S, Insperger T, Arnaud L et al (2011) Suppression of period doubling chatter in high-speed milling by spindle speed variation. Mach Sci Technol 15(2):153-171
[59] Morita H, Yamashita T (2012) Tracing and visualizing variation of chatter for in-process identification of preferred spindle speeds. Procedia CIRP 4:11-16
[60] Ismail F, Kubica E (1995) Active suppression of chatter in peripheral milling part 1. A statistical indicator to evaluate the spindle speed modulation method. Int J Adv Manuf Technol 10(5):299-310
[61] Kubica E, Ismail F (1996) Active suppression of chatter in peripheral milling. Part II. Application of fuzzy control. Int J Adv Manuf Technol 12(4):236-245
[62] Yilmaz A, Al-Regib E, Ni J (2002) Machine tool chatter suppression by multi-level random spindle speed variation. J Manuf Sci Eng 124(2):208-216
[63] Seguy S, Insperger T, Arnaud L et al (2010) On the stability of high-speed milling with spindle speed variation. Int J Adv Manuf Technol 48(9):883-895
[64] Ding L, Sun Y, Xiong Z (2018) Online chatter suppression in turning by adaptive amplitude modulation of spindle speed variation. J Manuf Sci Eng 140(12):121003. https://doi.org/10.1115/1.4041248
[65] Wang C, Zhang X, Yan R et al (2019) Multi harmonic spindle speed variation for milling chatter suppression and parameters optimization. Precis Eng 55:268-274
[66] Lv S, Zhao Y (2021) Stability of milling process with variable spindle speed using Runge-Kutta-based complete method. Math Probl Eng 2021:6672513. https://doi.org/10.1155/2021/6672513
[67] Otto A, Radons G (2013) Application of spindle speed variation for chatter suppression in turning. CIRP J Manuf Sci Technol 6(2):102-109
[68] Yamato S, Ito T, Matsuzaki H et al (2018) Programmable optimal design of sinusoidal spindle speed variation for regenerative chatter suppression. Procedia Manuf 18:152-160
[69] Yamato S, Ito T, Matsuzaki H et al (2020) Self-acting optimal design of spindle speed variation for regenerative chatter suppression based on novel analysis of internal process energy behavior. Int J Mach Tool Manuf 159:103639. https://doi.org/10.1016/j.ijmachtools.2020.103639
[70] Ding L, Sun Y, Xiong Z (2020) Active chatter suppression in turning by simultaneous adjustment of amplitude and frequency of spindle speed variation. J Manuf Sci Eng 142(2):021004. https://doi.org/10.1115/1.4045618
[71] Paek R, Ha SH, Ri SC (2023) Optimal determination of spindle speed variation type for the suppression of chatter in turning. Int J Adv Manuf Technol 126(5/6):2481-2496
[72] Albertelli P, Musletti S, Leonesio M et al (2012) Spindle speed variation in turning: technological effectiveness and applicability to real industrial cases. Int J Adv Manuf Technol 62(1):59-67
[73] Nam S, Hayasaka T, Jung H et al (2021) Proposal of novel spindle speed variation profile with constant acceleration rate for improvement of chatter stability. Precis Eng 68:218-234
[74] Guo Y, Lin B, Wang W (2019) Optimization of variable helix cutter for improving chatter stability. Int J Adv Manuf Technol 104(5):2553-2565
[75] Jin G, Qi H, Li Z et al (2018) Dynamic modeling and stability analysis for the combined milling system with variable pitch cutter and spindle speed variation. Commun Nonlinear Sci Numer Simul 63:38-56
[76] Jin G, Zhang Q, Hao S et al (2013) (2013) Stability prediction of milling process with variable pitch cutter. Math Probl Eng 1:932013. https://doi.org/10.1155/2013/932013
[77] Tehranizadeh F, Koca R, Budak E (2019) Investigating effects of serration geometry on milling forces and chatter stability for their optimal selection. Int J Mach Tool Manuf 144:103425. https://doi.org/10.1016/j.ijmachtools.2019.103425
[78] Altintas Y, Engin S, Budak E (1999) Analytical stability prediction and design of variable pitch cutters. J Manuf Sci Eng 121:173-178
[79] Turner S, Merdol D, Altintas Y et al (2007) Modelling of the stability of variable helix end mills. Int J Mach Tool Manuf 47(9):1410-1416
[80] Jin G, Zhang X, Zhang K et al (2020) Stability analysis method for periodic delay differential equations with multiple distributed and time-varying delays. Math Probl Eng 2020:1982363. https://doi.org/10.1155/2020/1982363
[81] Jin G, Jiang H, Han J et al (2021) Stability analysis of milling process with variable spindle speed and pitch angle considering helix angle and process phase difference. Math Probl Eng 2021:6654176. https://doi.org/10.1155/2021/6654176
[82] Sims N, Mann B, Huyanan S (2008) Analytical prediction of chatter stability for variable pitch and variable helix milling tools. J Sound Vib 317(3/5):664-686
[83] Otto A, Rauh S, Ihlenfeldt S et al (2017) Stability of milling with non-uniform pitch and variable helix tools. Int J Adv Manuf Technol 89(9):2613-2625
[84] Yan Z, Zhang C, Jiang X et al (2020) Chatter stability analysis for milling with single-delay and multi-delay using combined high-order full-discretization method. Int J Adv Manuf Technol 111(5):1401-1413
[85] Mei Y, Mo R, Sun H et al (2020) Stability analysis of milling process with multiple delays. Appl Sci 10(10):3646. https://doi.org/10.3390/app10103646
[86] Niu J, Ding Y, Zhu L et al (2017) Mechanics and multi-regenerative stability of variable pitch and variable helix milling tools considering runout. Int J Mach Tool Manuf 123:129-145
[87] Yusoff AR, Sims ND (2011) Optimisation of variable helix tool geometry for regenerative chatter mitigation. Int J Mach Tool Manuf 51(2):133-141
[88] Nie W, Zheng M, Yu H et al (2022) Analysis of vibration reduction mechanism for variable pitch end mills. Int J Adv Manuf Technol 119:7787-7797
[89] Comak A, Budak E (2017) Modeling dynamics and stability of variable pitch and helix milling tools for development of a design method to maximize chatter stability. Precis Eng 47:459-468
[90] Yang WA, Huang C (2020) Stability analysis of 2-D of milling dynamics for simultaneously varying tooth pitch and spindle speed with helix angle effect. Int J Adv Manuf Technol 110(5):1163-1177
[91] Tehranizadeh F, Budak E (2017) Design of serrated end mills for improved productivity. Procedia CIRP 58:493-498
[92] Wang JJJ, Yang C (2003) Angle and frequency domain force models for a roughing end mill with a sinusoidal edge profile. Int J Mach Tool Manuf 43(14):1509-1520
[93] Merdol S, Altintas Y (2004) Mechanics and dynamics of serrated cylindrical and tapered end mills. J Manuf Sci Eng 126(2):317-326
[94] Dombovari Z, Altintas Y, Stepan G (2010) The effect of serration on mechanics and stability of milling cutters. Int J Mach Tool Manuf 50(6):511-520
[95] Koca R, Budak E (2013) Optimization of serrated end mills for reduced cutting energy and higher stability. Procedia CIRP 8:570-575
[96] Grabowski R, Denkena B, K?hler J (2014) Prediction of process forces and stability of end mills with complex geometries. Procedia CIRP 14:119-124
[97] Bari P, Kilic ZM, Law M et al (2021) Rapid stability analysis of serrated end mills using graphical-frequency domain methods. Int J Mach Tool Manuf 171:103805. https://doi.org/10.1016/j.ijmachtools.2021.103805
[98] Farahani ND, Altintas Y (2022) Chatter stability of serrated milling tools in frequency domain. J Manuf Sci Eng 144(3):031013. https://doi.org/10.1115/1.4052007
[99] Brecher C, Baumler S, Brockmann B (2013) Avoiding chatter by means of active damping systems for machine tools. J Mach Eng 13(3):117-128
[100] Wan M, Liang XY, Yang Y et al (2020) Suppressing vibrations in milling-trimming process of the platelike workpiece by optimizing the location of vibration absorber. J Mater Process Technol 278:116499. https://doi.org/10.1016/j.jmatprotec.2019.116499
[101] Yuan H, Wan M, Yang Y et al (2019) A tunable passive damper for suppressing chatters in thin-wall milling by considering the varying modal parameters of the workpiece. Int J Adv Manuf Technol 104(9):4605-4616
[102] Heng Y, Min W, Yun Y (2019) Design of a tunable mass damper for mitigating vibrations in milling of cylindrical parts. Chin J Aeronaut 32(3):748-758
[103] Wang M (2011) Feasibility study of nonlinear tuned mass damper for machining chatter suppression. J Sound Vib 330(9):1917-1930
[104] Qin P, Liu Y, Wang M et al (2021) Milling vibration control of semiconical shell workpiece with multiple distribution tuned mass dampers. Int J Adv Manuf Technol 115(7):2175-2190
[105] Nakano Y, Kishi T, Takahara H (2021) Experimental study on application of tuned mass dampers for chatter in turning of a thin-walled cylinder. Appl Sci 11(24):12070. https://doi.org/10.3390/app112412070