Abstract
Determining grinding conditions to achieve part quality and production rate requirements is a challenging task. Due to the complexity of the process and many affecting factors, grinding conditions are chosen conservatively, mostly based on experience or handbooks to eliminate quality problems. Thus, an integrated modeling system is required to select grinding conditions in a systematic approach for high-performance grinding. The key feature required of such a system is the capability of producing results in a wide range of grinding conditions and parameters without the necessity of conducting extensive experimentation. This is feasible only by adopting geometrical-physical-based modeling for grinding which is a challenging task since most of the grinding process research is based on experimental methods involving calibration tests. In this study, by considering a grit representation of the grinding wheel and grit-workpiece interaction coupled with the material deformation model, a multi-dimensional modeling system capable of process predictions for a wide range of grinding parameters and conditions has been developed. Using this system, a digital twin-based framework is established to select grinding conditions in an efficient and proactive manner. Based on the simulation results of this new integrated system, some general guidelines are recommended with a systematic approach. This approach is demonstrated in a case study considering the process constraints showing how the material removal rate (MRR) can be maximized without sacrificing the surface integrity which is the main concern in this process. The proposed methodology offers a new outlook on grinding parameter selection, to be used in an integrated digital twin to increase part quality and productivity while respecting the constraints.
Similar content being viewed by others
References
Altintas, Y., Kersting, P., Biermann, D., Budak, E., Denkena, B., & Lazoglu, I. (2014). Virtual process systems for part machining operations. CIRP Annals, 63(2), 585–605. https://doi.org/10.1016/j.cirp.2014.05.007
Altintas, Y. (2016). Virtual High Performance Machining. Procedia CIRP, 46, 372–378. https://doi.org/10.1016/j.procir.2016.04.154
Brinksmeier, E., Aurich, J. C., Govekar, E., Heinzel, C., Hoffmeister, H., & Klocke, F. (2006). Advances in Modeling and Simulation of Grinding Processes. CIRP Annals, 55(1), 667–696. https://doi.org/10.1016/j.cirp.2006.10.003
Childs, T., Maekawa, K., Obikawa, T., & Yamane, Y. (2000). Tool damage. Metal Machining, 118–135. https://doi.org/10.1016/B978-0-08-052402-3.50007-1. Elsevier
Conroy, R. (2015). Sample size A rough guide https://doi.org/10.13140/RG.2.2.30497.51043
Curtis, D., Krain, H., Winder, A., & Novovic, D. (2021). Impact of grinding wheel specification on surface integrity and residual stress when grinding Inconel 718. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 235(10), 1668–1681. https://doi.org/10.1177/0954405420961209
De Bartolomeis, A., Newman, S. T., Jawahir, I. S., Biermann, D., & Shokrani, A. (2021). Future research directions in the machining of Inconel 718. Journal of Materials Processing Technology, 297, 117260. https://doi.org/10.1016/j.jmatprotec.2021.117260
De Oliveira, D., Da Silva, R. B., & Gelamo, R. V. (2019). Influence of multilayer graphene platelet concentration dispersed in semi-synthetic oil on the grinding performance of Inconel 718 alloy under various machining conditions. Wear, 426–427, 1371–1383. https://doi.org/10.1016/j.wear.2019.01.114
González, H., Calleja, A., Pereira, O., Ortega, N., López de Lacalle, L. N., & Barton, M. (2018). Super Abrasive Machining of Integral Rotary Components Using Grinding Flank Tools. Metals, 8(1), 24. https://doi.org/10.3390/met8010024
Guo, C., Ranganath, S., McIntosh, D., & Elfizy, A. (2008). Virtual high performance grinding with CBN wheels. CIRP Annals - Manufacturing Technology, 57(1), 325–328. https://doi.org/10.1016/j.cirp.2008.03.071
HILLIER, F. S., & LIEBERMAN, G. J. (2004). Introduction to Operations Research. McGraw-Hill S (seventh.)
Howes, T. D., Neailey, K., Harrison, A. J., & McKeown, P. A. (1987). Fluid Film Boiling in Shallow Cut Grinding. CIRP Annals, 36(1), 223–226. https://doi.org/10.1016/S0007-8506(07)62591-8
Inasaki, I., Karpuschewski, B., & Lee, H. S. (2001). Grinding chatter - Origin and suppression. CIRP Annals - Manufacturing Technology, 50(2), 515–534. https://doi.org/10.1016/S0007-8506(07)62992-8
Jaeger, J. C. (1942). Moving sources of heat and the temperature at sliding contacts. Proceedings of the Royal Society of New South Wales, 76, 203–224. https://doi.org/10.1109/TCST.2018.2852743
Jamshidi, H., & Budak, E. (2018). Grinding temperature modeling based on a time dependent heat source. Procedia CIRP, 77, 299–302. https://doi.org/10.1016/j.procir.2018.09.020
Jamshidi, H., Gurtan, M., & Budak, E. (2019). Identification of active number of grits and its effects on mechanics and dynamics of abrasive processes. Journal of Materials Processing Technology, 273, 116239. https://doi.org/10.1016/j.jmatprotec.2019.05.020
Jamshidi, H., & Budak, E. (2020). An analytical grinding force model based on individual grit interaction. Journal of Materials Processing Technology, 32, 116700. https://doi.org/10.1016/j.jmatprotec.2020.116700
Jamshidi, H., & Budak, E. (2021a). On the prediction of surface burn and its thickness in grinding processes. CIRP Annals. https://doi.org/10.1016/j.cirp.2021.04.041
Jamshidi, H., & Budak, E. (2021b). A 3D analytical thermal model in grinding considering a periodic heat source under dry and wet conditions. Journal of Materials Processing Technology, 295(March), 117158. https://doi.org/10.1016/j.jmatprotec.2021.117158
Kadivar, M., Azarhoushang, B., & Krajnik, P. (2021). Modeling of micro-grinding forces considering dressing parameters and tool deflection. Precision Engineering, 67, 269–281. https://doi.org/10.1016/j.precisioneng.2020.10.004
Li, G. F., Wang, L. S., & Yang, L. B. (2002). Multi-parameter optimization and control of the cylindrical grinding process. Journal of Materials Processing Technology, 129(1–3), 232–236. https://doi.org/10.1016/S0924-0136(02)00607-6
Li, H. N., & Axinte, D. (2017). On a stochastically grain-discretised model for 2D/3D temperature mapping prediction in grinding. International Journal of Machine Tools and Manufacture, 116, 60–76. https://doi.org/10.1016/j.ijmachtools.2017.01.004
Malkin, S., & Guo (1998). Grinding Technology (Vol. 3)
Martínez-Ciudad, A., López de Lacalle, L. N., & Sánchez, J. (2014). Uncertainty Propagation in the Grinding Process of High Contact Ratio Gears for a Planetary Geared Turbofan. New Advances in Mechanisms, Transmissions and Applications. Mechanisms and Machine Science, vol 17. Springer, Dordrecht.https://doi.org/10.1007/978-94-007-7485-8_8
Pecherer, E., & Malkin, S. (1984). Grinding of Steels with Cubic Boron Nitride (CBN). CIRP Annals, 33(1), 211–216. https://doi.org/10.1016/S0007-8506(07)61411-5
Rao, Z., Ding, W., Zhu, Y., & Su, H. (2019). Understanding the self-sharpening characteristics of polycrystalline cubic boron nitride super-abrasive in high-speed grinding of Inconel 718. Ceramics International, 45(10), 13324–13333. https://doi.org/10.1016/j.ceramint.2019.04.024
Rowe, W. B., Bell, W. F., Brough, D., & Davies, B. J. (1986). Optimization Studies in High Removal Rate Centreless Grinding. CIRP Annals - Manufacturing Technology, 35(1), 235–238. https://doi.org/10.1016/S0007-8506(07)61878-2
Rowe, B. W. (2014). Principles of Modern Grinding Technology: Vol-2
Saini, D. P. (1990). Wheel hardness and local elastic deflections in grinding. International Journal of Machine Tools and Manufacture, 30(4), 637–649. https://doi.org/10.1016/0890-6955(90)90013-9
Shi, Z., & Malkin, S. (2003). An Investigation of Grinding with Electroplated CBN Wheels. CIRP Annals, 52(1), 267–270. https://doi.org/10.1016/S0007-8506(07)60581-2
Shi, Z., & Malkin, S. (2006). Wear of Electroplated CBN Grinding Wheels. Journal of Manufacturing Science and Engineering, 128(1), 110–118. https://doi.org/10.1115/1.2122987
Stark, R., & Damerau, T. (2019). Digital Twin. In S. Chatti, & T. Tolio (Eds.), CIRP Encyclopedia of Production Engineering. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-35950-7_16870-1
Yastıkcı, B., Jamshidi, H., & Budak, E. (2016). Experimental Investigation of Wear Mechanisms with Electroplated CBN Wheel. ISAAT (pp.1–7)
Yu, T., Bastawros, A. F., & Chandra, A. (2017). Experimental and modeling characterization of wear and life expectancy of electroplated CBN grinding wheels. International Journal of Machine Tools and Manufacture, 121, 70–80. https://doi.org/10.1016/j.ijmachtools.2017.04.013
Zhang, J., Ge, P., Jen, T. C., & Zhang, L. (2009). Experimental and numerical studies of AISI1020 steel in grind-hardening. International Journal of Heat and Mass Transfer, 52(3–4), 787–795. https://doi.org/10.1016/j.ijheatmasstransfer.2008.06.037
Zhang, X., Lin, B., & Xi, H. (2013). Validation of an analytical model for grinding temperatures in surface grinding by cup wheel with numerical and experimental results. International Journal of Heat and Mass Transfer, 58(1–2), 29–42. https://doi.org/10.1016/j.ijheatmasstransfer.2012.11.022
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Ethical statement
The authors have no relevant financial or non-financial interests to disclose. No funding was received to assist with the preparation of this manuscript.
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Jamshidi, H., Budak, E. A digital twin-based framework for selection of grinding conditions towards improved productivity and part quality. J Intell Manuf 35, 161–173 (2024). https://doi.org/10.1007/s10845-022-02031-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10845-022-02031-x