Error compensation is an economical and effective technique for achieving high machining accuracy. However, a new phenomenon has been detected in its application: error-compensation excited vibrations and further decreased surface quality in some cases. The mechanism of this phenomenon is important but remains unclear, and its main influencing factor remains an open question. To reveal this mechanism, a stability and surface quality analysis model of the dynamic milling process that considers the influence of error compensation is proposed for the first time. Error compensation can be considered as a quasi-static, periodic forcing term added to the milling system. The quasi-static part changes the cutting width, whereas the periodic forcing part mainly influences the instantaneous undeformed chip thickness, based on which the milling stability and surface location error are derived. Numerical simulations and milling experiments were conducted to validate the proposed model. The experimental results show that error compensation has little influence on milling stability but may decrease the surface quality when the compensation values between compensation cycles change significantly. The proposed method shows great potential for estimating and optimizing error compensation paths and improving the quality of machined surfaces.
The full text can be downloaded at https://doi.org/10.1007/s40436-024-00537-6
Guan-Yan Ge
,
Yu-Kun Xiao
,
Jun Lv
,
Zheng-Chun Du
. Mechanism analysis and suppression for chatter and surface location error induced by error compensation[J]. Advances in Manufacturing, 2025
, 13(4)
: 750
-767
.
DOI: 10.1007/s40436-024-00537-6
[1] Munoa J, Beudaert X, Dombovari Z et al (2016) Chatter suppression techniques in metal cutting. CIRP Ann 65:785-808
[2] Du Z, Ge G, Xiao Y et al (2021) Modeling and compensation of comprehensive errors for thin-walled parts machining based on on-machine measurement. Int J Adv Manuf Technol 115:3645-3656
[3] Yang J, Yuan J, Ni J (1999) Thermal error mode analysis and robust modeling for error compensation on a CNC turning center. Int J Mach Tools Manuf 39:1367-1381
[4] Deng M, Li H, Xiang S et al (2020) Geometric errors identification considering rigid-body motion constraint for rotary axis of multi-axis machine tool using a tracking interferometer. Int J Mach Tools Manuf 158:103625. https://doi.org/10.1016/j.ijmachtools.2020.103625
[5] Ge G, Du Z, Feng X et al (2020) An integrated error compensation method based on on-machine measurement for thin web parts machining. Precis Eng 63:206-213. https://doi.org/10.1016/j.precisioneng.2020.03.002
[6] Zhu M, Ge G, Feng X et al (2021) A novel error compensation method for multistage machining processes based on differential motion vector sets of multiple contour points. J Manuf Sci Eng Trans ASME 143:1-14. https://doi.org/10.1115/1.4049036
[7] Altintas Y, Budak E (1995) Analytical prediction of stability lobes in milling. CIRP Ann Manuf Technol 44:357-362
[8] Budak E, Altintas Y (1998) Analytical prediction of chatter stability in milling—part I: general formulation. J Dyn Syst Meas Control Trans ASME 120:22-30
[9] Budak E, Altintas Y (1998) Analytical prediction of chatter stability in milling—part II: application of the general formulation to common milling systems. J Dyn Syst Meas Control Trans ASME 120:31-36
[10] Altintas Y, Stepan G, Merdol D et al (2008) Chatter stability of milling in frequency and discrete time domain. CIRP J Manuf Sci Technol 1:35-44
[11] Insperger T, Stépán G (2004) Updated semi-discretization method for periodic delay-differential equations with discrete delay. Int J Numer Methods Eng 61:117-141
[12] Ding Y, Zhu L, Zhang X et al (2020) A full-discretization method for prediction of milling stability. Int J Mach Tools Manuf 50:502-509
[13] Mann BP, Young KA, Schmitz TL et al (2005) Simultaneous stability and surface location error predictions in milling. J Manuf Sci Eng Trans ASME 127:446-453
[14] Dong X, Qiu Z (2020) Stability analysis in milling process based on updated numerical integration method. Mech Syst Signal Process 137:106435. https://doi.org/10.1016/j.ymssp.2019.106435
[15] Dong X, Shen X, Fu Z (2021) Stability analysis in turning with variable spindle speed based on the reconstructed semi-discretization method. Int J Adv Manuf Technol 117:3393-3403
[16] Sun Y, Jiang S (2018) Predictive modeling of chatter stability considering force-induced deformation effect in milling thin-walled parts. Int J Mach Tools Manuf 135:38-52
[17] Niu J, Jia J, Sun Y et al (2020) Generation mechanism and quality of milling surface profile for variable pitch tools considering runout. J Manuf Sci Eng Trans ASME 142:121001. https://doi.org/10.1115/1.4047622
[18] Dang X, Wan M, Zhang W et al (2021) Chatter analysis and mitigation of milling of the pocket-shaped thin-walled workpieces with viscous fluid. Int J Mech Sci 194:106214. https://doi.org/10.1016/j.ijmecsci.2020.106214
[19] Dang X, Wan M, Zhang W et al (2022) Stability analysis of the milling process of the thin floor structures. Mech Syst Signal Process 165:108311. https://doi.org/10.1016/j.ymssp.2021.108311
[20] Friedrich J, Hinze C, Renner A et al (2017) Estimation of stability lobe diagrams in milling with continuous learning algorithms. Robot Comput Integr Manuf 43:124-134
[21] Liu X, Li Y, Chen G (2019) Multimode tool tip dynamics prediction based on transfer learning. Robot Comput Integr Manuf 57:146-154
[22] Chen G, Li Y, Liu X (2019) Pose-dependent tool tip dynamics prediction using transfer learning. Int J Mach Tools Manuf 137:30-41
[23] Liu Y, Altintas Y (2022) Predicting the position-dependent dynamics of machine tools using progressive network. Precis Eng 73:409-422
[24] Yan Z, Zhang C, Jia J et al (2022) High-order semi-discretization methods for stability analysis in milling based on precise integration. Precis Eng 73:71-92
[25] Yuan J, Ni J (1998) The real-time error compensation technique for CNC machining systems. Mechatronics 8:359-380
[26] Chen J, Yuan J, Ni J et al (1993) Real-time compensation for time-variant volumetric errors on a machining center. J Manuf Sci Eng Trans ASME 115:472-479
[27] 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
[28] Munoa J, Beudaert X, Erkorkmaz K et al (2015) Active suppression of structural chatter vibrations using machine drives and accelerometers. CIRP Ann 64:385-388
[29] Rashid A, Nicolescu CM (2006) Active vibration control in palletised workholding system for milling. Int J Mach Tools Manuf 46:1626-1636
[30] Gourc E, Seguy S, Arnaud L (2011) Chatter milling modeling of active magnetic bearing spindle in high-speed domain. Int J Mach Tools Manuf 51:928-936
[31] Wang C, Zhang X, Liu Y et al (2018) Stiffness variation method for milling chatter suppression via piezoelectric stack actuators. Int J Mach Tools Manuf 124:53-66
[32] Zhang X, Yin Z, Gao J et al (2019) Discrete time-delay optimal control method for experimental active chatter suppression and its closed-loop stability analysis. J Manuf Sci Eng Trans ASME 141:051003. https://doi.org/10.1115/1.4043020
[33] Gao J, Caliskan H, Altintas Y (2019) Sensorless control of a three-degree-of-freedom ultrasonic vibration tool holder. Precis Eng 58:47-56
[34] Li X, Wan S, Yuan J et al (2021) Active suppression of milling chatter with LMI-based robust controller and electromagnetic actuator. J Mater Process Technol 297:117238. https://doi.org/10.1016/j.jmatprotec.2021.117238
[35] Dong X, Li X, Zhang L et al (2023) Chatter suppression analysis for variable pitch cutter in milling. Int J Adv Manuf Technol 131:3193-3203. https://doi.org/10.1007/s00170-023-11887-z
[36] Wang X, Ma P, Peng X et al (2020) Study on vibration suppression performance of a flexible fixture for a thin-walled casing. Int J Adv Manuf Technol 106:4281-4291
[37] 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 Eng Trans ASME 134(6):061006. https://doi.org/10.1115/1.4007622
[38] Ge G, Du Z, Yang J (2020) Rapid prediction and compensation method of cutting force-induced error for thin-walled workpiece. Int J Adv Manuf Technol 106:5453-5462
[39] Rubeo MA, Schmitz TL (2016) Mechanistic force model coefficients: a comparison of linear regression and nonlinear optimization. Precis Eng 45:311-321
