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Wheel wear-related instability in grinding of quartz glass

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Abstract

Grinding is a popular method for producing high-quality parts made of hard and brittle materials. A lot of researchers have focused on the impact of grinding parameters on surface quality. However, only a few studies discussed the surface quality instability caused by the grinding wheel wear during a long grinding process. In this paper, through wheel state monitoring and surface quality testing of ground samples, it is found that the relationship between ground surface roughness and theoretical undeformed chip thickness is significantly affected by the grinding wheel wear state rather than maintain steady as described in most available models. By introducing the normal grinding force, a linear relationship was found among normal grinding force, undeformed chip thickness, and ground surface roughness. Besides, sensitivity analysis was conducted to guide the parameter adjustment to maintain the stability of ground surface roughness and grinding state. The mechanism of the effect of wheel wear on normal grinding force was also studied in detail. This study will help to further understand the mechanism of the influence of wheel wear on the grinding stability.

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Data Availability

The authors confirm that the data supporting the findings of this study are available within the article.

Abbreviations

a p :

Depth of cut

C :

Number of cutting points per area

d e :

Equivalent diameter of grinding wheel

D :

Diameter of the grinding wheel

E(R a ) :

Expected value of surface roughness Ra

E(t) :

Expected value of undeformed chip thickness

f :

Overlap factor

F n :

Normal grinding force

h w :

Reduction of abrasive grits protrusion height caused by grinding wheel wear

k :

Synthesized parameter of Vs, Vw and Ap

MRV 41Cr4 :

Material removal volume of 41Cr4 in the preparation of wear grinding wheel

N d :

Number of dynamic active grits

P 0 :

Constant determined by experiment

r :

Aspect ratio of the chip section

R a :

Arithmetical mean roughness of grinding surface

S w :

Tip area of the worn grit

t m :

Maximum undeformed chip thickness

v s :

Grinding wheel speed

v w :

Workpiece infeed rate

δ n ,n + 1 :

Change rate in normal grinding force between wear stage n and wear stage n + 1

ϕ :

A coefficient fitted according to experimental data

References

  1. Li HN, Axinte D (2017) On a stochastically grain-discretised model for 2D/3D temperature mapping prediction in grinding. Int J Mach Tools Manuf 116:60–76. https://doi.org/10.1016/j.ijmachtools.2017.01.004

    Article  Google Scholar 

  2. Malkin S, Guo CS (2008) Grinding technology: theory and applications of machining with abrasives, 2nd edn. Industrial Press, New York

    Google Scholar 

  3. Tahvilian AM, Liu ZH, Champliaud H, Hazel B, Lagacé M (2015) Characterization of grinding wheel grain topography under different robotic grinding conditions using confocal microscope. Int J Adv Manuf Technol 80:1159–1171. https://doi.org/10.1007/s00170-015-7109-z

    Article  Google Scholar 

  4. Esmaeilzare A, Rahimi A, Rezaei SM (2014) Investigation of subsurface damages and surface roughness in grinding process of Zerodur glass-ceramic. Appl Surf Sci 313:67–75. https://doi.org/10.1016/j.apsusc.2014.05.137

    Article  Google Scholar 

  5. Wu CJ, Li BZ, Liu Y, Liang SY (2017) Surface roughness modeling for grinding of silicon carbide ceramics considering co-existence of brittleness and ductility. Int J Mech Sci 133:167–177. https://doi.org/10.1016/j.ijmecsci.2017.07.061

    Article  Google Scholar 

  6. Zhu CM, Gu P, Wu YY, Liu DH, Wang XK (2019) Surface roughness prediction model of SiCp/Al composite in grinding. Int J Mech Sci 155:98–109. https://doi.org/10.1016/j.ijmecsci.2019.02.025

    Article  Google Scholar 

  7. Seeman M, Ganesan G, Karthikeyan R, Velayudham A (2010) Study on tool wear and surface roughness in machining of particulate aluminum metal matrix composite-response surface methodology approach. Int J Adv Manuf Technol 48:613–624. https://doi.org/10.1007/s00170-009-2297-z

    Article  Google Scholar 

  8. Liu W, Deng ZH, Shang YY, Wan LL (2017) Effects of grinding parameters on surface quality in silicon nitride grinding. Ceram Int 43:1571–1577. https://doi.org/10.1016/j.ceramint.2016.10.135

    Article  Google Scholar 

  9. Öztürk S, Kahraman MF (2019) Modeling and optimization of machining parameters during grinding of flat glass using response surface methodology and probabilistic uncertainty analysis based on Monte Carlo simulation. Measurement 145:274–291. https://doi.org/10.1016/j.measurement.2019.05.098

    Article  Google Scholar 

  10. Sahin Y, Motorcu AR (2005) Surface roughness model for machining mild steel with coated carbide tool. Mater Design 26:321–326. https://doi.org/10.1016/j.matdes.2004.06.015

    Article  Google Scholar 

  11. Saravanakumar A, Dhanabal S, Jayanand E, Logeshwaran P (2018) Analysis of process parameters in surface grinding process. Mater Today Proc 5:8131–8137. https://doi.org/10.1016/j.matpr.2017.11.500

    Article  Google Scholar 

  12. Agarwal S (2016) Optimizing machining parameters to combine high productivity with high surface integrity in grinding silicon carbide ceramics. Ceram Int 42:6244–6262. https://doi.org/10.1016/j.ceramint.2016.01.008

    Article  Google Scholar 

  13. Pan YH, Wang YH, Zhou P, Yan Y, Guo DM (2020) Activation functions selection for BP neural network model of ground surface roughness. J Intell Manuf. https://doi.org/10.1007/s10845-020-01538-5

    Article  Google Scholar 

  14. Agarwal S, Rao PV (2010) Modeling and prediction of surface roughness in ceramic grinding. Int J Mach Tools Manuf 50:1065–1076. https://doi.org/10.1016/j.ijmachtools.2010.08.009

    Article  Google Scholar 

  15. Khare SK, Angrwal S (2015) Predictive modeling of surface roughness in grinding. Procedia CIRP 31:375–380. https://doi.org/10.1016/j.procir.2015.04.092

    Article  Google Scholar 

  16. Sun JL, Chen P, Qin F, An T, Yu HP, He BF (2018) Modeling and experimental study of roughness in silicon wafer self-rotating grinding. Precis Eng 51:625–637. https://doi.org/10.1016/j.precisioneng.2017.11.003

    Article  Google Scholar 

  17. Liu YM, Warkentin A, Bauer R, Gong YD (2013) Investigation of different grain shapes and dressing to predict surface roughness in using kinematic simulations. Precis Eng 37:758–764. https://doi.org/10.1016/j.precisioneng.2013.02.009

    Article  Google Scholar 

  18. Zhou LB, Ebina Y, Wu K, Shimizu J, Onuki T, Ojima H (2017) Theoretical analysis on effects of grain size variation. Precis Eng 50:27–31. https://doi.org/10.1016/j.precisioneng.2017.04.010

    Article  Google Scholar 

  19. Novoselov Y, Bratan S, Bogutsky V (2016) Analysis of relation between grinding wheel wear and abrasive grains wear. Procedia Eng 150:809–814. https://doi.org/10.1016/j.proeng.2016.07.116

    Article  Google Scholar 

  20. Zhang QL, Zhao QL, To S, Guo B, Zhai WJ (2017) Diamond wheel wear mechanism and its impact on the surface generation in parallel diamond grinding of RB-SiC/Si. Diam Relat Mater 74:16–23. https://doi.org/10.1016/j.diamond.2017.01.019

    Article  Google Scholar 

  21. Jeon S, Zolfaghari A, Lee C (2018) Dicing wheel wear monitoring technique utilizing edge diffraction effect. Measurement 121:139–143. https://doi.org/10.1016/j.measurement.2018.02.057

    Article  Google Scholar 

  22. Naik DN, Mathew NT, Vijayaraghavan L (2019) Wear of electroplated super abrasive CBN wheel during grinding of Inconel 718 super alloy. J Manuf Process 43:1–8. https://doi.org/10.1016/j.jmapro.2019.04.033

    Article  Google Scholar 

  23. Sutowski P, Plichta S (2006) An investigation of the grinding wheel wear with the use of root-mean-square value of acoustic emission. Arch Civ Mech Eng 6(1):87–98. https://doi.org/10.1016/S1644-9665(12)60078-8

    Article  Google Scholar 

  24. Arun A, Rameshkumar K, Unnikrishnan D, Sumesh A (2018) Tool condition monitoring of cylindrical grinding process using acoustic emission sensor. Mater Today: Proc 5:11888–11899. https://doi.org/10.1016/j.matpr.2018.02.162

    Article  Google Scholar 

  25. Varghese B, Pathare S, Gao R, Guo C, Malkin S (2000) Development of a sensor-integrated “intelligent” grinding wheel for in-process monitoring. Ann CIRP 49(1):231–234. https://doi.org/10.1016/S0007-8506(07)62935-7

    Article  Google Scholar 

  26. Shen JY, Wang JQ, Jiang B, Xu XP (2015) Study on wear of diamond wheel in ultrasonic vibration-assisted grinding ceramics. Wear 332–333:788–793. https://doi.org/10.1016/j.wear.2015.02.047

    Article  Google Scholar 

  27. Kannan K, Arunachalam N (2018) Grinding wheel redress life estimation using force and surface texture analysis. Procedia CIRP 72:1439–1444. https://doi.org/10.1016/j.procir.2018.03.031

    Article  Google Scholar 

  28. Zhang YB, Li CH, Ji HJ, Yang XH, Yang M, Jia DZ, Zhang XP, Li RZ, Wang J (2017) Analysis of grinding mechanics and improved prediction force model based on material-removal and plastic-stacking mechanisms. Int J Mach Tools Manuf 122:81–97. https://doi.org/10.1016/j.ijmachtools.2017.06.002

    Article  Google Scholar 

  29. Zhou WB, Su HH, Dai JB, Yu TF, Zheng YH (2018) Numerical investigation on the influence of cutting-edge radius and grinding wheel speed on chip formation in SiC grinding. Ceram Int 44:21451–21460. https://doi.org/10.1016/j.ceramint.2018.08.206

    Article  Google Scholar 

  30. Selvaraj DP, Chandramohan P, Mohanraj M (2014) Optimization of surface roughness, cutting force and tool wear of nitrogen alloyed duplex stainless steel in a dry turning process using Taguchi method. Measurement 49:205–215. https://doi.org/10.1016/j.measurement.2013.11.037

    Article  Google Scholar 

  31. Agarwal S, Rao PV (2013) Predictive modeling of force and power based on a new analytical undeformed chip thickness model in ceramics grinding. Int J Mach Tools Manuf 65:68–78. https://doi.org/10.1016/j.ijmachtools.2012.10.006

    Article  Google Scholar 

  32. Zhu DH, Xu XH, Yang ZY, Zhuang KJ, Yan SJ, Ding H (2018) Analysis and assessment of robotic belt grinding mechanism by force modeling and force control experiment. Tribol Int 120:93–98. https://doi.org/10.1016/j.triboint.2017.12.043

    Article  Google Scholar 

  33. Li SY, Wang Z, Wu YL (2008) Relationship between subsurface damage and surface roughness of optical materials in grinding and lapping processes. J Mater Process Tech 205:24–41. https://doi.org/10.1016/j.jmatprotec.2007.11.118

    Article  Google Scholar 

  34. Shen JY, Wang JQ, Jiang B, Xu XP (2015) Study on wear of diamond wheel in ultrasonic vibration-assisted grinding ceramic. Wear 332–333:788–793. https://doi.org/10.1016/j.wear.2015.02.047>

  35. Patidar A, Mandal AK, Chaudhary AK, Jain V (2021) Surface roughness of sintered yttria stabilised zirconia (YSZ) using high speed moderate depth super-abrasive grinding. Mater Today: Proc 44:2705–2709. https://doi.org/10.1016/j.matpr.2020.12.686

    Article  Google Scholar 

  36. Zhao LL (2013) High efficient precision grinding of optical glass with the coarse-grained diamond wheel. Ph. D Thesis, Harbin: Harbin Institute of Technology. https://kns.cnki.net/kcms/detail/detail.aspx?FileName=1014080669.nh&DbName=CDFD2014 (In Chinese version)

  37. Kitzig H, Tawakoli T, Azarhoushang B (2016) A novel ultrasonic-assisted dressing method of electroplated grinding wheels via stationary diamond dresser. Int J Adv Manuf Technol 86:487–494. https://doi.org/10.1007/s00170-015-8156-1

    Article  Google Scholar 

  38. Ding WF, Dai CW, Yu TB, Xu JH, Fu YC (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

    Article  Google Scholar 

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Acknowledgements

All authors appreciate the financial support from the National Natural Science Foundation of China (51875078, 51991372, 51975094) and the Science Fund for Creative Research Groups of NSFC of China (51621064).

Funding

The National Natural Science Foundation of China (Grant nos. 51875078, 51991372, and 51975094) and the Science Fund for Creative Research Groups of NSFC of China (Grant no. 51621064).

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Ping Zhou, Ying Yan, and Dongming Guo developed the idea for the study, Yonghao Wang and Yuhang Pan did the analyses, and Yonghao Wang wrote the paper.

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Correspondence to Ping Zhou.

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Wang, Y., Zhou, P., Pan, Y. et al. Wheel wear-related instability in grinding of quartz glass. Int J Adv Manuf Technol 119, 233–245 (2022). https://doi.org/10.1007/s00170-021-08189-7

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