Abstract
The quality of ground surface is closely related with the interaction behavior between the ground component and the grains in grinding wheel. Normally, the grains have the characteristics of irregular shape, nonuniform size and random distribution. Thus, the material removal mechanism generated from the interaction behavior in grinding is difficult to directly observe through experiment. This research presents a multi-scale model to capture the interaction state of the grain-workpiece by determining the transient stage of each individual grain based on the actual grinding wheel structure and grinding condition. Different from the previous models of the single-grain grinding, it provides a fresh perspective to theoretically improve the quality of ground surface by incorporating the multi-scale interactive behavior, active transition, and continuous evolution of the grain-workpiece during the grinding process. The predicted forces are compared with the experimental data performed in the research, and also with those in literature. It shows that the maximum error is less than 14%. The proposed model enables it possible to address the multiple effects of grinding parameters, grain size, grain location, and distribution on the transient stage of the active grains in the grinding zone. Therefore, based on the proposed multi-scale model, the innovative approach is revealed to improve the quality of ground surface by modifying the interaction state of the grain-workpiece through the analytical analysis of multi-level parameters related with grinding wheel structure and grinding process.
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References
Hecker RL, Liang SY (2003) Predictive modeling of surface roughness in grinding. Int J Mach Tools Manuf 43:755–761. https://doi.org/10.1016/S0890-6955(03)00055-5
Cai C, An Q, Ming W, Chen M (2021) Modelling of machined surface topography and anisotropic texture direction considering stochastic tool grinding error and wear in peripheral milling. J Mater Process Technol 292:117065. https://doi.org/10.1016/j.jmatprotec.2021.117065
Huang H, Yin L, Zhou L (2003) High speed grinding of silicon nitride with resin bond diamond wheels. J Mater Process Technol 141:329–336. https://doi.org/10.1016/S0924-0136(03)00284-X
Inasaki I (2007) Principles of abrasive processing. Mach Sci Technol 0344:1–3. https://doi.org/10.1080/10940349808945664
Malkin S (1991) Grinding technology: theory and applications of machining with abrasives. Int J Mach Tools Manuf 31:435–436. https://doi.org/10.1016/0890-6955(91)90088-K
Dai C, Ding W, Xu J, Fu Y, Yu T (2017) Influence of grain wear on material removal behavior during grinding nickel-based superalloy with a single diamond grain. Int J Mach Tools Manuf 113:49–58. https://doi.org/10.1016/j.ijmachtools.2016.12.001
Dai C, Yin Z, Ding W, Zhu Y (2019) Grinding force and energy modeling of textured monolayer CBN wheels considering undeformed chip thickness nonuniformity. Int J Mech Sci 157–158:221–230. https://doi.org/10.1016/j.ijmecsci.2019.04.046
Zhu D, Song S, Qu C, Lv Y, Wu C (2020) Numerical investigation of crack initiation, propagation and suppression in robot-assisted abrasive belt grinding of zirconia ceramics via an improved chip-thickness model. Ceram Int 46:22030–22039. https://doi.org/10.1016/j.ceramint.2020.05.199
Setti D, Kirsch B, Aurich JC (2017) An analytical method for prediction of material deformation behavior in grinding using single grit analogy. Procedia CIRP 58:263–268. https://doi.org/10.1016/j.procir.2017.03.193
Malekian M, Mostofa MG, Park SS, Jun MBG (2012) Modeling of minimum uncut chip thickness in micro machining of aluminum. J Mater Process Technol 212:553–559. https://doi.org/10.1016/j.jmatprotec.2011.05.022
Hou ZB, Komanduri R (2003) On the mechanics of the grinding process – part I. Stochastic nature of the grinding process. Int J Mach Tools Manuf 43:1579–1593. https://doi.org/10.1016/S0890-6955(03)00186-X
Jiang J, Ge P, Hong J (2013) Study on micro-interacting mechanism modeling in grinding process and ground surface roughness prediction. Int J Adv Manuf Technol 67:1035–1052. https://doi.org/10.1007/s00170-012-4546-9
Wang D, Ge P, Bi W, Jiang J (2014) Grain trajectory and grain workpiece contact analyses for modeling of grinding force and energy partition. Int J Adv Manuf Technol 70:2111–2123. https://doi.org/10.1007/s00170-013-5428-5
Ding W, Dai C, Yu T, Xu J, Fu Y (2017) Grinding performance of textured monolayer CBN wheels: undeformed chip thickness nonuniformity modeling and ground surface topography prediction. Int J Mach Tools Manuf 122:66–80. https://doi.org/10.1016/j.ijmachtools.2017.05.006
Zhang Y, Fang C, Huang G, Xu X (2018) Modeling and simulation of the distribution of undeformed chip thicknesses in surface grinding. Int J Mach Tools Manuf 127:14–27. https://doi.org/10.1016/j.ijmachtools.2018.01.002
Li HN, Yu TB, Wang ZX, Zhu LD, Wang WS (2017) Detailed modeling of cutting forces in grinding process considering variable stages of grain-workpiece micro interactions. Int J Mech Sci 126:319–339. https://doi.org/10.1016/j.ijmecsci.2016.11.016
Sun Y, Su Z, Gong Y, Ba D, Yin G, Zhang H, Zhou L (2021) Analytical and experimental study on micro-grinding surface-generated mechanism of DD5 single-crystal superalloy using micro-diamond pencil grinding tool. Arch Civ Mech Eng 21:1–22. https://doi.org/10.1007/s43452-020-00163-6
Setti D, Arrabiyeh PA, Kirsch B, Heintz M, Aurich JC (2020) Analytical and experimental investigations on the mechanisms of surface generation in micro grinding. Int J Mach Tools Manuf 149:103489. https://doi.org/10.1016/j.ijmachtools.2019.103489
Park HW, Liang SY (2008) Force modeling of micro-grinding incorporating crystallographic effects. Int J Mach Tools Manuf 48:1658–1667. https://doi.org/10.1016/j.ijmachtools.2008.07.004
Chang HC, Wang JJJ (2008) A stochastic grinding force model considering random grit distribution. Int J Mach Tools Manuf 48:1335–1344. https://doi.org/10.1016/j.ijmachtools.2008.05.012
Wang L, Pan J, Shao Y, Zeng Q, Ding X (2021) Two new kurtosis-based similarity evaluation indicators for grinding chatter diagnosis under non-stationary working conditions. Meas J Int Meas Confed 176:109215. https://doi.org/10.1016/j.measurement.2021.109215
Kishore K, Chauhan SR, Sinha MK (2023) Application of machine learning techniques in environmentally benign surface grinding of Inconel 625. Tribol Int 188:108812. https://doi.org/10.1016/j.triboint.2023.108812
Zhang T, Yuan C, Zou Y (2022) Online optimization method of controller parameters for robot constant force grinding based on deep reinforcement learning rainbow. J Intell Robot Syst 105:85. https://doi.org/10.1007/s10846-022-01688-z
Macerol N, Franca LFP, Krajnik P (2020) Effect of the grit shape on the performance of vitrified-bonded CBN grinding wheel. J Mater Process Technol 277. https://doi.org/10.1016/j.jmatprotec.2019.116453
Dang J, Zhang H, An Q, Ming W, Chen M (2021) On the microstructural evolution pattern of 300 M steel subjected to surface cryogenic grinding treatment. J Manuf Process 68:169–185. https://doi.org/10.1016/j.jmapro.2021.05.026
Le ZW, Duan F, Zhang X, Zhu Z, Ju BF (2018) A new diamond machining approach for extendable fabrication of micro-freeform lens array. Int J Mach Tools Manuf 124:134–148. https://doi.org/10.1016/j.ijmachtools.2017.10.007
De Vathaire M, Delamare F, Felder E (1981) An upper bound model of ploughing by a pyramidal indenter. Wear 66:55–64. https://doi.org/10.1016/0043-1648(81)90032-6
Younis M, Sadek MM, El-Wardani T (1987) A new approach to development of a grinding force model. J Manuf Sci Eng Trans ASME 109:306–313. https://doi.org/10.1115/1.3187133
Behera BC, Chetan SD, Ghosh S, Rao PV (2017) Spreadability studies of metal working fluids on tool surface and its impact on minimum amount cooling and lubrication turning. J Mater Process Technol 244:1–16. https://doi.org/10.1016/j.jmatprotec.2017.01.016
Jiménez H, Staia MH, Puchi ES (1999) Mathematical modeling of a carburizing process of a SAE 8620H steel. Surf Coatings Technol 120–121:358–365. https://doi.org/10.1016/S0257-8972(99)00464-8
Anderson D, Warkentin A, Bauer R (2011) Experimental and numerical investigations of single abrasive-grain cutting. Int J Mach Tools Manuf 51:898–910. https://doi.org/10.1016/j.ijmachtools.2011.08.006
Öpöz TT, Chen X (2012) Experimental investigation of material removal mechanism in single grit grinding. Int J Mach Tools Manuf 63:32–40. https://doi.org/10.1016/j.ijmachtools.2012.07.010
Agarwal S (2019) On the mechanism and mechanics of wheel loading in grinding. J Manuf Process 41:36–47. https://doi.org/10.1016/j.jmapro.2019.03.009
Durgumahanti USP, Singh V, Rao PV (2010) A new model for grinding force prediction and analysis. Int J Mach Tools Manuf 50:231–240. https://doi.org/10.1016/j.ijmachtools.2009.12.004
Yao CF, Jin QC, Huang XC, Wu DX, Ren JX, Zhang DH (2013) Research on surface integrity of grinding inconel718. Int J Adv Manuf Technol 65:1019–1030. https://doi.org/10.1007/s00170-012-4236-7
Tang J, Du J, Chen Y (2009) Modeling and experimental study of grinding forces in surface grinding. J Mater Process Technol 209:2847–2854. https://doi.org/10.1016/j.jmatprotec.2008.06.036
Hao ZP, Li JN, Fan YH (2021) Research on deformation mechanism of cutting nickel-based superalloy Inconel718 based on strain gradient theory. J Manuf Sci Eng Trans ASME 143:1–15. https://doi.org/10.1115/1.4050552
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This research was supported by Xueping Zhang from the National Natural Science Foundation of China under the project No. 52075335 and No. 51675339.
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Xueping Zhang is responsible for ensuring that the descriptions are accurate and agreed by all authors. The role(s) of all authors are listed as follows:
Conceptualization: Xueping Zhang and Xin Li
Methodology: Xin Li and Xueping Zhang
Modeling based on software: Xin Li
Validation: Xin Li
Formal analysis: Xin Li and Xueping Zhang
Investigation: Xin Li and Xueping Zhang
Resources: Xueping Zhang and Zhenqiang Yao
Data curation: Xin Li
Writing of original draft: Xin Li
Writing including review and editing: Xueping Zhang
Visualization: Xin Li and Xueping Zhang
Supervision: Xueping Zhang, Rajiv Shivpuri, and Zhenqiang Yao
Project administration: Xueping Zhang and Rajiv Shivpuri
Funding acquisition: Xueping Zhang and Rajiv Shivpuri
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Li, X., Zhang, X., Shivpuri, R. et al. A multi-scale model revealed in the grinding process and its influence on the grinding force and surface integrity. Int J Adv Manuf Technol 130, 2811–2832 (2024). https://doi.org/10.1007/s00170-023-12739-6
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DOI: https://doi.org/10.1007/s00170-023-12739-6