A digital solution for slender workpiece turning: the DRITTO project
Niccolò Grossi, Antonio Scippa, Lorenzo Sallese, Lorenzo Morelli, Gianni Campatellidownload PDF
Abstract. Turning slender components is a critical task since workpiece flexibility entails relevant deformations during the process, leading to potential loss of accuracy, lower machining efficiency and higher manufacturing costs. The DRITTO project aims at developing an easy-to-use digital solution to support manufacturing of flexible axisymmetric components. The proposed support system, starting from the not-optimized toolpath, stock geometry and tool parameters, it will compute the optimized toolpath by integrating three different modules: a) workpiece FE modelling, b) turning process modelling, c) toolpath optimization. The project is ongoing, but, at the current stage, preliminary validation of the proposed solution has been carried out. DRITTO is funded as an experiment of DIH-World Horizon2020 project, and the consortium is composed by the machining services SME Meccanica Ceccarelli & Rossi and the University of Florence as part of the Digital Innovation Hub ARTES4.0.
Turning, Tool Path, Stiffness
Published online 9/5/2023, 9 pages
Copyright © 2023 by the author(s)
Published under license by Materials Research Forum LLC., Millersville PA, USA
Citation: Niccolò Grossi, Antonio Scippa, Lorenzo Sallese, Lorenzo Morelli, Gianni Campatelli, A digital solution for slender workpiece turning: the DRITTO project, Materials Research Proceedings, Vol. 35, pp 486-494, 2023
The article was published as article 57 of the book Italian Manufacturing Association Conference
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 Y. Altintas, Manufacturing Automation: Metal Cutting Mechanics, Machine Tool Vibrations, and CNC Design, (2012).
 Y. Altintas, O. Tuysuz, M. Habibi, Z.L. Li, Virtual compensation of deflection errors in ball end milling of flexible blades, CIRP Ann. 67 (2018) 365–368. https://doi.org/10.1016/j.cirp.2018.03.001
 S. Liu, J. Bao, P. Zheng, A review of digital twin-driven machining: From digitization to intellectualization, J. Manuf. Syst. 67 (2023) 361–378. https://doi.org/10.1016/j.jmsy.2023.02.010
 Z. Zhu, X. Xi, X. Xu, Y. Cai, Digital Twin-driven machining process for thin-walled part manufacturing, J. Manuf. Syst. 59 (2021) 453–466. https://doi.org/10.1016/j.jmsy.2021.03.015
 S. Afazov, D. Scrimieri, Chatter model for enabling a digital twin in machining, Int. J. Adv. Manuf. Technol. 110 (2020) 2439–2444. https://doi.org/10.1007/s00170-020-06028-9
 N. Grossi, L. Sallese, A. Scippa, G. Campatelli, Speed-varying cutting force coefficient identification in milling, Precis. Eng. 42 (2015) 321–334. https://doi.org/10.1016/j.precisioneng.2015.04.006
 L. V Colwell, Predicting the Angle of Chip Flow for Single-Point Cutting Tools, Trans. Am. Soc. Mech. Eng. 76 (2022) 199–203. v10.1115/1.4014795
 P.G. Benardos, G.C. Vosniakos, Prediction of surface roughness in CNC face milling using neural networks and Taguchi’s design of experiments, Robot. Comput. Integr. Manuf. 18 (2002) 343–354. https://doi.org/10.1016/S0736-5845(02)00005-4
 G. Jianliang, H. Rongdi, A united model of diametral error in slender bar turning with a follower rest, Int. J. Mach. Tools Manuf. 46 (2006) 1002–1012. https://doi.org/10.1016/j.ijmachtools.2005.07.042
 J.R.R. Mayer, A.-V. Phan, G. Cloutier, Prediction of diameter errors in bar turning: a computationally effective model, Appl. Math. Model. 24 (2000) 943–956. https://doi.org/10.1016/S0307-904X(00)00027-5
 M. Soori, B. Arezoo, M. Habibi, Tool Deflection Error of Three-Axis Computer Numerical Control Milling Machines, Monitoring and Minimizing by a Virtual Machining System, J. Manuf. Sci. Eng. 138 (2016). https://doi.org/10.1115/1.4032393
 A. Ertürk, H.N. Özgüven, E. Budak, 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. Tools Manuf. 46 (2006) 1901–1912. https://doi.org/10.1016/j.ijmachtools.2006.01.032