A novel experimental-numerical approach to modeling machine tool dynamics for chatter stability prediction

Chatter is one of the main limitations to milling performances. Prediction of such unstable phenomenon via stability lobe diagrams requires the measurement of the Frequency Response Functions (FRFs) for each tool and machine tool setup. This paper presents a hybrid FE-experimental approach to identify tool-tip FRFs with only one set of measurements, taking into account tool change without any other experimental test. Machine tool dynamics is modeled using a Finite Element (FE) approach. Machine, spindle and tool-holder are described by a lumped model characterized by frequency-dependent stiffness, while the tool is FE modeled. Lumped model and tool are connected by means of stiffness matrices extracted using the Craig-Bampton dynamic reduction method. The obtained simplified model of machine tool enables chatter prediction by means of stability lobe diagram for different tool without the need for extensive experimentation. Once a new tool is clamped no other measurements are needed, just the new tool FE model. Experimental validation under different conditions is provided, showing accuracy and reliability of proposed approach.

[1]  Jokin Munoa,et al.  Receptance coupling for tool point dynamic prediction by fixed boundaries approach , 2014 .

[2]  Ryuta Sato,et al.  Spindle speed ramp-up test: A novel experimental approach for chatter stability detection , 2015 .

[3]  Yusuf Altintas,et al.  Chatter Stability in Turning and Milling with in Process Identified Process Damping , 2010 .

[4]  Michele Monno,et al.  A new receptance coupling substructure analysis methodology to improve chatter free cutting conditions prediction , 2013 .

[5]  Gianni Campatelli,et al.  3D Finite Element Modeling of Holder-Tool Assembly for Stability Prediction in Milling☆ , 2015 .

[6]  Giuseppe Catania,et al.  Theoretical–experimental modeling of milling machines for the prediction of chatter vibration , 2011 .

[7]  Gianni Campatelli,et al.  Speed-varying cutting force coefficient identification in milling , 2015 .

[8]  Takashi Matsumura,et al.  Dynamic Characteristics in The Cutting Operations with Small Diameter End Mills , 2008 .

[9]  Svetan Ratchev,et al.  Effects of micro-milling conditions on the cutting forces and process stability , 2013 .

[10]  Guillem Quintana,et al.  Chatter in machining processes: A review , 2011 .

[11]  Manfred Weck,et al.  Chatter Stability of Metal Cutting and Grinding , 2004 .

[12]  Ryuta Sato,et al.  Optimal workpiece orientation to reduce the energy consumption of a milling process , 2015 .

[13]  M. Bampton,et al.  Coupling of substructures for dynamic analyses. , 1968 .

[14]  Yusuf Altintas,et al.  Receptance coupling for end mills , 2003 .

[15]  Erhan Budak,et al.  Analytical modeling of spindle-tool dynamics on machine tools using Timoshenko beam model and receptance coupling for the prediction of tool point FRF , 2006 .

[16]  Reza Madoliat,et al.  Modeling and Analysis of Frictional Damper Effect on Chatter Suppression in a Slender Endmill Tool , 2011 .

[17]  Bin Rong,et al.  Feasibility Study on the Minimum Quantity Lubrication in High-Speed Helical Milling of Ti-6Al-4V , 2012 .

[18]  Yusuf Altintas,et al.  Analytical Prediction of Stability Lobes in Milling , 1995 .

[19]  Tony L. Schmitz,et al.  Predicting High-Speed Machining Dynamics by Substructure Analysis , 2000 .

[20]  Chunzheng Duan,et al.  Surface roughness prediction of end milling process based on IPSO-LSSVM , 2014 .

[21]  Gianni Campatelli,et al.  Chatter Stability Prediction in Milling Using Speed-varying Cutting Force Coefficients☆ , 2014 .