Abstract
Machining is one of the important manufacturing processes used in industry. Dynamic interaction between the tool and the workpiece may lead to the occurrence of chatter vibrations, which are associated with problems of poor surface finish, reduced workpiece quality, and low productivity. In the past, researchers developed some important methods to investigate the dynamics of machining processes. Dynamic responses of cutting systems were firstly identified by means of sensors, followed by chatter stability analysis using stability lobe diagrams to determine the stable and unstable regions, and finally, chatters were suppressed by either active or passive dam** techniques. Previous reviews emphasized on identification of the chatter vibration with less focus on control. This paper mainly reviews the state of the art on the control of machining chatter vibrations, including dam** methods related to boring, turning, and milling processes.
Similar content being viewed by others
References
Quintana G, Ciurana J (2011) Chatter in machining processes: a review. Int J Mach Tools Manuf 51:363–376
Altintas Y (2012) Manufacturing automation, 2nd edn. Cambridge University Press, NY, USA
Akazawa K, Shamoto E (2008) Study on regenerative chatter vibration in ball end milling of flexible workpieces, Nagoya, Japan
Tlusty J, Andrews GC (1983) A critical review of sensors for unmanned machining. CIRP Ann Manuf Technol 32:563–572
Siddhpura M, Paurobally R (2012) A review of chatter vibration research in turning. Int J Mach Tools Manuf 61:27–47
Khatri BC, Rathod P, Valaki JB (2015) Ultrasonic vibration-assisted electric discharge machining: a research review. Proc Inst Mech Eng B J Eng Manuf 230:319–330
Ma L, Melkote SN, Castle JB (2013a) A model-based computationally efficient method for on-line detection of chatter in milling. J Manuf Sci Eng 135:1–11
Li S, Wang X, **e L, Pang S, Peng S, Liang Z, Jiao L (2015a) The milling-milling machining method and its realization. Int J Adv Manuf Technol 76:1151–1161
Pop PA (2008) The study of cutting forces about dynamic stability of milling machine tools. In: Proceedings of the 9th biennial ASME conference on engineering systems design and analysis, Haifa, Israel, pp 617–626
Okafor AC, Talekar VR, Irigireddy V, Gulati R (2010) Development of web-based virtual CNC milling machine tool with mechanistic cutting force models for education and learning. In: Proceedings of the ASME 2010 World Conference on Innovative Virtual Reality, Ames, Iowa, USA, pp 153–163
Fekrmandi H, Unal M, Baghalian A, Tashakori S, Oyola K, Alsenawi A, Tansel IN (2016) A non-contact method for part-based process performance monitoring in end milling operations. Int J Adv Manuf Technol 83:13–20
Toh CK (2004) Vibration analysis in high speed rough and finish milling hardened steel. J Sound Vib 278:101–115
Kaldestad KB, Tyapin I Hovland G (2015) Robotic face milling path correction and vibration reduction, Korea, Busan
Sinou JJ, Jezequel L (2007) Mode coupling instability in friction-induced vibrations and its dependency on system parameters including dam**. Eur J Mech A Solids 26:106–122
Ast A, Braun S, Eberhard P, Heisel U (2007) Adaptronic vibration dam** for machine tools. CIRP Ann Manuf Technol 56:379–382
van Dijk NJM, van de Wouw N, Doppenberg EJJ, Oosterling HAJ, Nijmeijer H (2012) Robust active chatter control in the high-speed milling process. IEEE Trans Control Syst Technol 20:901–917
Karkoub M (2011) Robust control of the elastodynamic vibrations of a flexible rotor system with discontinuous friction. Journal of Vibration and Acoustics 501(1–9):133:034
Tsai NC, Shih LW, Lee RM (2010a) Spindle vibration suppression for advanced milling process by using self-tuning feedback control. Int J Adv Manuf Technol 48:1–10
Gȯrges D, Kroneis J, Liu S (2008) Active vibration control of storage and retrieval machines. In: ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Brooklyn, New York, USA, pp 1037–1046
Morimoto Y, Suzuki N, Kaneko Y, Isobe M (2014) Vibration control of relative tool-spindle displacement for computer numerically controlled lathe with pipe frame structure. J Manuf Sci Eng 502(1–4):136:044
Radecki PP, Farinholt KM, Park G, Bement MT (2010) Vibration suppression in cutting tools using a collocated piezoelectric sensor/actuator with an adaptive control algorithm. J Vib Acoust 132 002(1–8):051
Inoue T, Ishida Y, Niimi H (2012) Vibration analysis of a self-excited vibration in a rotor system caused by a ball balancer. J Vib Acoust 006(1–11):134:021
van Dijk NJM, van de Wouw N, Nijmeijer H (2015) Fixed-structure robust controller design for chatter mitigation in high-speed milling. Int J Robust Nonlinear Control 25:3495–3514
Chen M, Knospe CR (2007) Control approaches to the suppression of machining chatter using active magnetic bearings. IEEE Trans Control Syst Technol 15:220–232
Dohner JL, Lauffer JP, Hinnerichs TD, Shankar N, Regelbrugge M, Kwan CM, Xu R, Winterbauer B, Bridger K (2004) Mitigation of chatter instabilities in milling by active structural control. J Sound Vib 269:197–211
Munoa J, Beudaert X, Erkorkmaz K, Iglesias A, Barrios A, Zatarain M (2015) Active suppression of structural chatter vibrations using machine drives and accelerometers. CIRP Ann Manuf Technol 64:385–388
Lu X, Chen F, Altintas Y (2014) Magnetic actuator for active dam** of boring bars. CIRP Ann Manuf Technol 63:369–372
Chen F, Lu X, Altintas Y (2014) A novel magnetic actuator design for active dam** of machining tools. International Journal of Machine Tools Manufacture 85:58–69
Chen F, Hanifzadegan M, Altintas Y, Lu X (2015) Active dam** of boring bar vibration with a magnetic actuator. IEEE/ASME Transactions on Mechatronics 20(6):2783–2794
Chen F (2014) Active dam** of machine tools with magnetic actuators. PhD thesis, University Of British Columbia
Khorasani AM, Jalali Aghchai A, Khorram A (2011) Chatter prediction in turning process of conical workpieces by using case-based resoning (CBR) method and Taguchi design of experiment. Int J Adv Manuf Technol 55:457–464
Koohestani A, Mo JPT (2012) The application of image correlation in order to define chatter during milling of titanium. In: Proceedings of the ASME 2012 international mechanical engineering congress and exposition, Houston, Texas,USA, pp 1955–1958
Tangjitsitcharoen S, Pongsathornwiwat N (2013) Development of chatter detection in milling processes. Int J Adv Manuf Technol 65:919–927
Tangjitsitcharoen S, Saksri T, Ratanakuakangwan S (2015) Advance in chatter detection in ball end milling process by utilizing wavelet transform. J Intell Manuf 26:485–499
Abele E, Sielaff T, Schiffler A (2012) Method for chatter detection with standard plc systems. Prod Eng 6:611–619
Nair U, Krishna BM, Namboothiri VNN, Nampoori VPN (2010) Permutation entropy based real-time chatter detection using audio signal in turning process. Int J Adv Manuf Technol 46:61–68
Kim DH, Song JY, Cha SK, Son H (2011) The development of embedded device to detect chatter vibration in machine tools and CNC-based autonomous compensation. J Mech Sci Technol 25:2623–2630
Lamraoui M, Barakat M, Thomas M, El Badaoui M (2015) Chatter detection in milling machines by neural network classification and feature selection. J Vib Control 21:1251–1266
Tarng YS, Chen MC (1994) An intelligent sensor for detection of milling chatter. J Intell Manuf 5:193–200
Tansel IN, Li M, Demetgul M, Bickraj K, Kaya B, Ozcelik B (1994) Detecting chatter and estimating wear from the torque of end milling signals by using index based reasoner (IBR). Int J Adv Manuf Technol 58:109–118
Li HZ, **g XB, Wang J (2014) Detection and analysis of chatter occurrence in micro-milling process. J Eng Manuf 228:1359–1371
Wang M, Fei R (1999) Chatter suppression based on nonlinear vibration characteristic of electrorheological fluids. Int J Mach Tools Manuf 39:1925–1934
Mei D, Kong T, Shih AJ, Chen Z (2009) Magnetorheological fluid-controlled boring bar for chatter suppression. J Mater Process Technol 209:1861–1870
Wang M, Fei R (2001) On-line chatter detection and control in boring bar based on an electrorheological fluid. Mechatronics 11:779–792
Mackerle J (1999) Finite-element analysis and simulation of machining: a bibliography (1976-1996). J Mater Process Technol 86:17–44
Yan X, Huang S (2011) Research of four roll strip mill axial force based on the finite element simulation analysis. In: International Conference on Consumer Electronics, Communications and Networks (CECNet), **anNing, China, pp 564–568
Baker JR, Rouch KE (2002) Use of finite element structural models in analyzing machine tool chatter. Finite Elem Anal Des 38:1029–1046
Grossi N, Montevecchim F, Scippa A, Campatelli G (2015) 3D finite element modeling of holder-tool assembly for stability prediction in milling. 15th CIRP Conference on Modelling of Machining Operations (15th CMMO) 31:527–532
Cakir MC, Isik Y (2005) Finite element analysis of cutting tools prior to fracture in hard turning operations. Mater Des 26:105–112
Weiwei W (2009) Finite element analysis of dynamic characteristic for the XK717 CNC milling machine. In: International conference on measuring technology and mechatronics automation, ICMTMA, Zhangjiajie, Hunan, China, pp 803–805
Mahdavinejad R (2005) Finite element analysis of machine and workpiece instability in turning. Int J Mach Tools Manuf 45:753–760
Dirikolu MH, Childs THC, Maekawa K (2001) Finite element simulation of chip flow in metal machining. Int J Mech Sci 43:2699–2713
Liu H, Sun Y, Liang Y, Lu Z (2010) Three dimensional finite element simulation and analysis of residual stress in milling. In: 5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies, vol 551A, Harbin, China, pp 1–5
Sun YZ, Liu HT, Liang YC, Zhang Z (2010) Finite element simulation of material’s stress and strain in micro-milling. In: 4th International Seminar on Modern Cutting and Measurement Engineering, vol 973S, Bei**g, China, pp 1–6
Song Q, Ju G, Liu Z, Ai X (2014) Subdivision of chatter-free regions and optimal cutting parameters based on vibration frequencies for peripheral milling process. Int J Mech Sci 83:172–183
Insperger T, Gradisek J, Kalveram M, Stepan G, Winert K, Govekar E (2006) Machine tool chatter and surface location error in milling processes. J Manuf Sci Eng 128:913–920
Insperger T, Stepan G (2004) Updated semi-discretization method for periodic delay-differential equations with discrete delay. Int J Numer Methods Eng 61:117–141
Galdino dos Santos R, Teixeira Coelho R (2014) A contribution to improve the accuracy of chatter prediction in machine tools using the stability lobe diagram. J Manuf Sci Eng 136 005(1–7):021
Solis E, Peres CR, Jimenez JE, Alique JR, Monje JC (2004) A new analytical-experimental method for the identification of stability lobes in high-speed milling. Int J Mach Tools Manuf 44:1591–1597
Gagnol V, Bouzgarrou BC, Ray P, Barra C (2007) Stability-based spindle design optimization. J Manuf Sci Eng 129:407–415
Eynian M (2014). In: 6th CIRP international conference on high performance cutting, HPC2014 Frequency domain study of vibrations above and under stability lobes in machining systems, Trollhattan, Sweden, pp 164–169
Altintas Y, Budak E (1995) Analytical prediction of stability lobes in milling. CIRP Ann Manuf Technol 44:357–362
Altintas Y, Shamoto E, Lee P, Budak E (1999) Analytical prediction of stability lobes in ball end milling. J Manuf Sci Eng 121:586–592
Ismail F, Soliman E (1997) A new method for the identification of stability lobes in machining. Int J Mach Tools Manuf 37:763–774
Quintana G, Ciurana J, Teixidor D (2008) A new experimental methodology for identification of stability lobes diagram in milling operations. Int J Mach Tools Manuf 48:1637– 1645
Tsai NC, Chen DC, Lee RM (2010b) Chatter prevention for milling process by acoustic signal feedback. Int J Adv Manuf Technol 47:1013–1021
Abele E, Fiedler U (2004) Creating stability lobe diagrams during milling. CIRP Ann Manuf Technol 53:309–312
Zheng CM, Junz Wang JJ, Sung CF (2013) Analytical prediction of the critical depth of cut and worst spindle speeds for chatter in end milling. J Manuf Sci Eng 136 003(01–10):011
Elias A, Rodriguez CA, Delgadillo E, Martinez A, Araya F, Flores V (2005) Chatter prediction in orthogonal cutting based on Lambert function. In: ASME 2005 International Mechanical Engineering Congress and Exposition, Orlando, Florida USA, pp 1143–1147
Feng J, Sun Z, Jiang Z, Yang L (2016) Identification of chatter in milling of Ti-6Al-4V titanium alloy thin-walled workpieces based on cutting force signals and surface topography. Int J Adv Manuf Technol 82:1909–1920
Wan M, Zhang WH, Dang JW, Yang Y (2010) A unified stability prediction method for milling process with multiple delays. Int J Mach Tools Manuf 50:29–41
Wan M, Ma YC, Zhang WH, Yang Y (2015) Study on the construction mechanism of stablility lobes in milling process with multiple modes. Int J Adv Manuf Technol 79:589–603
Gasparetto A (1998) A system theory approach to mode coupling chatter in machining. J Dyn Syst Meas Contr 120:545–547
Zhang HT, Wu Y, He D, Zhao H (2015) Model predictive control to mitigate chatters in milling processes with input constraints. Int J Mach Tools Manuf 91:54–61
Mahnama M, Movahhedy MR (2010) Prediction of machining chatter based on FEM simulation of chip formation under dynamic conditions. Int J Mach Tools Manuf 50:611–620
Fischer A, Eberhard P (2014) Controlling vibrations of a cutting process using predictive control. Comput Mech 54:21–31
Wang M, Gao L, Zheng Y (2014) Prediction of regenerative chatter in the high-speed vertical milling of thin-walled workpiece made of titanium alloy. Int J Adv Manuf Technol 72:707–716
Sims ND (2015) Fast chatter stability prediction for variable helix milling tools. J Mech Eng Sci 230:133–144
Palanisamy P, Rajendran I, Shanmugasundaram S, Saravanan R (2006) Prediction of cutting force and temperature rise in the end-milling operation. Proc Inst Mech Eng B J Eng Manuf 220:1577–1587
Bissey-Breton S, Poulachon G, Lapujoulade F (2006) Integration of tool geometry in prediction of cutting forces during milling of hard materials. Proc Inst Mech Eng B J Eng Manuf 220:579–587
Li B, Cao Y, Ye X, Guan J, Yang J (2015b) Multi-scale prediction of the geometrical deviations of the surface finished by five-axis ball-end milling. Proc Inst Mech Eng B J Eng Manuf 220:1–18
Ramesh K, Alwarsamy T, Jayabal S (2015) Prediction of cutting process parameters in boring operations using artificial neural networks. J Vib Control 21:1043–1054
Moradi H, Movahhedy MR, Vossoughi G (2012) Tunable vibration absorber for improving milling stability with tool wear and process dam** effects. Mech Mach Theory 52:59–77
Rubio L, Ja Loya, Miguelez MH, Fernandez-Saez J (2013) Optimization of passive vibration absorbers to reduce chatter in boring. Mech Syst Sig Process 41:691–704
Huang B, Chen JC (2003) An in-process neural network-based surface roughness prediction (INN-SRP) system using a dynamometer in end milling operations. Int J Adv Manuf Technol 21:339–347
Susanto V, Chen JC (2003) Fuzzy logic based in-process tool-wear monitoring system in face milling operations. Int J Adv Manuf Technol 21:186–192
Chen JC, Chen JC (2005) An artificial neural networks based in process tool wear prediction system in milling operations. Int J Adv Manuf Technol 25:427–434
Faassen RPH, Van de Wouw N, Oosterling JAJ, Nijmeijer H (2003) Prediction of regenerative chatter by modelling and analysis of high-speed milling. Int J Mach Tools Manuf 43:1437–1446
Tatar K, Gren P (2016) Estimation of the in-plane vibrations of a rotating spindle, using out-of-plane laser vibrometry measurements. Mech Syst Sig Process 72-73:660–666
Galvan-Tejada CE, Galvan-Tejada I, Sandoval EI, Brena R (2012) Wifi bluetooth based combined positioning algorithm. Procedia Engineering 35:101–108
Rubio L, de la Sen M (2007) Adaptive control of milling forces under fractional order holds. In: Innovative Algorithms and Techniques in Automation, Industrial Electronics and Telecommunications, Apartado, Spain, pp 257–261
Kubica EG, Ismail F (1996) Active suppression of chatter in peripheral milling. part II. application of fuzzy control. Int J Adv Manuf Technol 12:236–245
Xu C, Shin YC (2008) An adaptive fuzzy controller for constant cutting force in end-milling processes. J Manuf Sci Eng 130 001(1–10):031
Brecher C, Manoharan D, Ladra U, Kopken HG (2010) Chatter suppression with an active workpiece holder. Prod Eng 4:239–245
Abele E, Hanselka H, Haase F, Schlote D, Schiffler A (2008) Development and design of an active work piece holder driven by piezo actuators. Prod Eng 2:437–442
Tansel I, Nedbouyan A, Trujillo M (1995) Design of a smart workpiece holder (swh)to extend the useful life of micro-tools. In: IECON, USA, pp 116–120
Cao HR, Zhang XW, Chen XF (2017) The concept and progress of intelligent spindles: a review. Int J Mach Tools Manuf 112:21–52
Saadabad NA, Moradi H, Vossoughi G (2014). Global optimization and design of dynamic absorbers for chatter suppression in milling process with tool wear and process dam**. 24th CIRP Design Conference 21:360–366
Martins da Silva M, Venter GS, Varoto PS, Coelho RT (2015) Experimental results on chatter reduction in turning through embedded piezoelectric material and passive shunt circuits. Mechatronics 29:78–85
Wan M, Ma YC, Feng J, Zhang WH (2016) Study of static and dynamic ploughing mechanisms by establishing generalized model with static milling forces. Int J Mech Sci 114:120– 131
Anderson CS, Semercigil SE, Turan OF (2007) A passive adaptor to enhance chatter stability for end mills. Int J Mach Tools Manuf 47:1777–1785
Moradi H, Vossoughi G, Behzad M, Movahhedy MR (2015) Vibration absorber design to suppress regenerative chatter in nonlinear milling process: application for machining of cantilever plates. Appl Math Model 39:600–620
Sun Y, Xu J (2015) Experiments and analysis for a controlled mechanical absorber considering delay effect. J Sound Vib 339:25–37
Sims ND (2007) Vibration absorbers for chatter suppression: a new analytical tuning methodology. J Sound Vib 301:592–607
Nakano Y, Takahara H, Yasue K, Asaga R (2012) The effect of multiple dynamic absorbers on regenerative chatter and resonance in end milling process. In: Proceeding ASME 45288, Houston, Texas, USA, pp 1–7
Bavastri CA, Polli ML, Voltolini DR, Presezniak FA (2015) A methodology to mitigate chatter through optimal viscoelastic absorber. J Eng Manuf 229:1348–1356
Asfar KR, Akour SN (2004) Optimization analysis of impact viscous damper for controlling self-excited vibrations. J Vib Control 11:103–120
Stone BJ, Andrew C (1969) Optimization of vibration absorbers: application to complex structures. J Mech Eng Sci 11:221–233
Hagood NW, Flotow AV (1991) Dam** of structural vibrations with piezoelectric materials and passive electrical networks. J Sound Vib 146:243–268
Shevtsov S, Soloviev A, Acopyan V, Samochenko I (2009) Helicopter rotor blade vibration control on the basis of active/passive piezoelectric dam** approach. In: 4Th international conference on physics and control (PHYSCON), Catania, Italy, pp 1–9
Yigit U, Cigeroglu E, Budak E (2013) Chatter reduction in turning by using piezoelectric shunt circuits. In: Proceedings of the 31st IMAC, A Conference on Structural Dynamics, California, USA, pp 415–420
Chen WM, Liu TS (2013) Modeling and experimental validation of new two degree-of-freedom piezoelectric actuators. Mechatronics 23:1163–1170
Giorgio Bort CM, Leonesio M, Bosetti P (2016) A model-based adaptive controller for chatter mitigation and productivity enhancement in CNC milling machines. Robot Comput Integr Manuf 40:34–43
Denkena B, Floter F (2012) Adaptive cutting force control on a milling machine with hybrid axis configuration. In: 3Rd CIRP conference on process machine interactions (3rd PMI), vol 4, pp 109–114
Ma Y, Zhang X, Xu M, **e S (2013b) Hybrid model based on preisach and support vector machine for novel dual-stack piezoelectric actuator. Mech Syst Sig Process 34:156–172
Zuperl U, Cus F, Reibenschuh M (2012) Modeling and adaptive force control of milling by using artificial techniques. J Intell Manuf 23:1805–1815
Chen Z, Zhang HT, Zhang X, Ding H (2013) Adaptive active chatter control in milling processes. J Dyn Syst Meas Contr 007(1–7):136:021
Bosetti P, Leonesio M, Parenti P (2013) On development of an optimal control system for real-time process optimization on milling machine tools. In: 8th CIRP Conference on Intelligent Computation in Manufacturing Engineering, Italy, pp 31–36
Monnin J, Kuster F, Wegener K (2014a) Optimal control for chatter mitigation in milling-part 1: modeling and control design. Control Eng Pract 24:156–166
Monnin J, Kuster F, Wegener K (2014b) Optimal control for chatter mitigation in milling-part 2: experimental validation. Control Eng Pract 24:167–175
Mei D, Yao Z, Kong T, Chen Z (2010) Parameter optimization of time-varying stiffness method for chatter suppression based on magnetorheological fluid-controlled boring bar. Int J Adv Manuf Technol 46:1071–1083
Moradi H, Vossoughi G, Movahhedy MR, Salarieh H (2013) Suppression of nonlinear regenerative chatter in milling process via robust optimal control. J Process Control 23:631–648
Kalinski KJ, Galewski MA (2011) Chatter vibration surveillance by the optimal-linear spindle speed control. Mech Syst Sig Process 25:383–399
Saravanamurugan S, Alwarsamy T, Devarajan K (2015) Optimization of damped dynamic vibration absorber to control chatter in metal cutting process. J Vib Control 21:949–958
Chodnicki M, Kalinski KJ, Galewski MA (2015) Vibration surveillance during milling flexible details with the use of active optimal control. Journal of Low Frequency Noise Vibration and Active Control 32:145–156
Kopac J, Pogacnik M (2000) Dynamic stabilization of the turn-milling process by parameter optimization. Proc Inst Mech Eng B J Eng Manuf 214:127–135
Chen F, Tzeng Y (2004) Optimization of the volumetric accuracy of high-speed computer numerical control milling with dynamic quality characteristics. J Eng Manuf 218:1741–1754
Pour DS, Behbahani S (2015) Semi-active fuzzy control of machine tool chatter vibration using smart MR dampers. Int J Adv Manuf Technol 83:421–428
Spencer Jr BF, Dyke SJ, Sain MK, Carlson JD (1997) Phenomenological model for magnetorheological dampers. J Eng Mech 123:230–238
Kim D, Jeon D (2011) Fuzzy-logic control of cutting forces in CNC milling processes using motor currents as indirect force sensors. Precis Eng 35:143–152
Tsai NC, Shih LW, Lee RM (2010c) Counterbalance of cutting force for advanced milling operations. Mech Syst Sig Process 24:1191–1208
Haber-Guerra R, Liang SY, Alique JR, Haber-Haber R (2006) Fuzzy control of spindle torque in high-speed milling processes. J Manuf Sci Eng 128:1014–1018
Xu C, Shin YC (2006) Control of cutting force for creep-feed grinding processes using a multi-level fuzzy controller. J Dyn Syst Meas Contr 129:480–492
Chen JC (1996) A fuzzy-nets tool-breakage detection system for end-milling operations. Int J Adv Manuf Technol 12:153–164
Zhao P, Shi Y, Huang J (2016) Proportional-integral based fuzzy sliding mode control of the milling head. Control Eng Pract 53:1–13
Mesina OS, Langari R (2001) A neuro-fuzzy system for tool condition monitoring in metal cutting. J Manuf Sci Eng 123:312– 318
Tandon V, El-Mounayri H (2001) A novel artificial neural networks force model for end milling. Int J Adv Manuf Technol 18:693–700
Zuperl U, Cus F, Reibenschuh M (2011) Neural control strategy of constant cutting force system in end milling. Rob Comput Integr Manuf 27:485–493
Lee S (2000) Specific cutting force coefficients modeling of end milling. KSE International Journal 14:622–632
Arnaiz-Gonzaez A, Fernandez-Valdivielso A, Bustillo A, Lopez de Lacalle LN (2016) Using artificial neural networks for the prediction of dimensional error on inclined surfaces manufactured by ball-end milling. Int J Adv Manuf Technol 83:847–859
Chen Y, Qiu J, Ji H, Zhu K (2010) Tracking control of piezoelectric actuator system using inverse hysteresis model. Int J Appl Electromagn Mech 33:1555–1564
Reddy R, Saha P (2016) Kautz filters based model predictive control for resonating systems. International Journal of Dynamics and Control 33:1–19
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Muhammad, B.B., Wan, M., Feng, J. et al. Dynamic dam** of machining vibration: a review. Int J Adv Manuf Technol 89, 2935–2952 (2017). https://doi.org/10.1007/s00170-016-9862-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-016-9862-z