Skip to main content
SpringerLink
Log in

Mechanism of a deterministic sponge figuring processing (SFP) in Ni–P surface formation considering the robustness of the tool influence function: modeling and experimental investigation

  • ORIGINAL ARTICLE
  • Published:
The International Journal of Advanced Manufacturing Technology Aims and scope Submit manuscript

Abstract

The core optics in the deep-space high-energy physics ray detection system are an ultra-precision aspherical surface, which would generate surface errors introduced by the ultra-precision single point diamond turning (SPDT), leaving the millimeter-level length and micron-level height periodic mid-spatial frequency (MSF) errors dissatisfying the expected optical performance. Hence, a corrective technique is urgent to effectively remove MSF errors from optical surfaces, enhancing the compliance control of the tool to adapt to curvature-varying optical surfaces to obtain a stable Gaussian-like removal function. This study explored the sponge figuring processing (SFP) removal mechanism, which verified the robustness and removal efficiency of the tool influence function for the planar and various curvatures of the Ni–P surface. To comprehensively investigate the removal function of SFP, based on the sponge-figuring process removal mechanism with three removal regimes, the relative velocity model and contact pressure model are established and verified for validity by pre-experiment. To obtain a stable and effective removal function, L16 orthogonal experiments and analysis of variance (ANOVA) methods were conducted on flat specimen surfaces on a 3-axis ultra-precision figuring tester machine utilizing a sponge head with in-situ correction of high slurry absorption and retention capacity as the figuring tool. To determine the curvature surface impact on the robustness of the tool influence function (TIF), matching experiments of spatial wavelength and full width at half maximum (FWHM) were executed. As a result, the removal function is mainly impacted by the offset, accounting for 40%, and the error was 8% in the predicted value of the volume removal rate under the optimal parameter conditions. From the perspective of optical performance, the significant peak of 1D-power spectral density (PSD) was suppressed in the mid-frequency band, partially converted into high-frequency band errors, and the mid-frequency surface ripple error was effectively enhanced from 2.4 to 1.8 nm, following multiple iterative figuring, for the variable curvature surface.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23

Similar content being viewed by others

Abbreviations

SPDT:

Single point diamond turning

PSD:

Power spectral density

APPP:

Atmospheric pressure plasma processing

LAM:

Laser-assisted machining

FJP:

Fluid jet polishing

MRF:

Magneto-rheological finishing

VAM:

Vibration-assisted micro-milling

SFP:

Sponge figuring process

PSF:

Point spread function

FEA:

Finite element analysis

H-S:

Harvey-Shark

XRS:

X-ray scattering

DT:

Diamond turning

STP:

Small tool polishing

CCOS:

Computer-controlled optical surfacing

MRD:

Maximum removal depth

HSF:

High-spatial frequency

ANOVA:

The analysis of variance

MRR:

Material removal rate

LSF:

Low-spatial frequency

TIF:

Tool influence function

SSD:

Suppressed subsurface damage

BP:

Bonnet polishing

FWHM:

The full width at half maximum

References

  1. Mir A, Luo X, Cheng K, Cox A (2018) Investigation of influence of tool rake angle in single point diamond turning of silicon. Int J Adv Manuf Technol 94(5–8):2343–2355

    Article  Google Scholar 

  2. Su X, Yue X (2022) Nonlinear dwell-time algorithm for freeform surface generation by atmospheric-pressure plasma processing. Opt Express 30:18348

    Article  PubMed  ADS  Google Scholar 

  3. Beaucamp A, Namba Y (2013) Super-smooth finishing of diamond turned hard X-ray molding dies by combined fluid jet and bonnet polishing. CIRP Ann 62(1):315–318

    Article  Google Scholar 

  4. Li G, Li Y, Liao Q, Xue J, Wang B (2022) Mechanism of dual-direction vibration-assisted (DVA) micro-milling in surface formation considering the tool life-lengthening effect on the Ti6Al4V: design and experiment. Int J Adv Manuf Technol 123(7–8):2313–2330

    Article  Google Scholar 

  5. Kotha A, Harvey J (1995) Scattering effects of machined optical surfaces. Proc SPIE 2541:54–65

    Article  ADS  Google Scholar 

  6. Harvey JE (1995) Scattering effects in x-ray imaging systems. Proc SPIE 2515:246–272

    Article  ADS  Google Scholar 

  7. Sironi G, Spiga D (2008) Surface roughness evaluation on mandrels and mirror shells for future X-ray telescopes. Proc SPIE 7011:701137

    Article  Google Scholar 

  8. Zhang H, Zhang N, Han W, Gilchrist MD, Fang F (2021) Investigation on a novel in-mould microcompression system for the precision replication of microlens arrays. J Manuf Processes 67:388–405

    Article  Google Scholar 

  9. Abrahams P (1994) Henry Fitz: A preeminent 19th century telescope maker. J Antique Telescope Soc 6:6–10

    ADS  Google Scholar 

  10. Karci Ö, Beldek TB (2021) Quantitative investigation of abrasive grit size dependency of subsurface damages for the metal-bonded abrasives on Zerodur glass-ceramic. Appl Opt 60:2624–2632

    Article  ADS  Google Scholar 

  11. Fess E, Ross J, Matthews G (2017) Grinding and polishing of conformal windows and domes. Proc SPIE 10179:101790Q

    Article  Google Scholar 

  12. Davis J, Champey P, Kolodziejczak J, Griffith C (2019) Deterministic polishing of replicating grazing-incidence mandrels. Proc SPIE 11119:111190U

    Google Scholar 

  13. Preston F (1927) The theory and design of plate glass polishing machines. J Glass Technol 11(44):214–256

    CAS  Google Scholar 

  14. Luo J, Dornfeld DA (2001) Material removal mechanism in chemical mechanical polishing: theory and modeling. IEEE Trans Semicond Manuf 14:112–133

    Article  Google Scholar 

  15. Evans CJ, Paul E, Dornfeld D, Lucca DA, Byrne G, Tricard M, Klocke F, Dambon O, Mullany BA (2003) Material removal mechanisms in lapping and polishing. CIRP Ann 52(2):611–633

    Article  Google Scholar 

  16. Pan R, Zhong B, Chen D, Wang Z, Fan J, Zhang C, Wei S (2018) Modification of tool influence function of bonnet polishing based on interfacial friction coefficient. Int J Mach Tool Manuf 124:43–52

    Article  Google Scholar 

  17. Schinhaerl M, Rascher R, Stamp R, Smith L, Smith G, Sperber P, Pitschke E (2008) Utilisation of time-variant influence functions in the computer controlled polishing. Precis Eng 32(1):47–54

    Article  Google Scholar 

  18. H. Li, G. Yu, D. Walker, R. Evans (2011) Modelling and measurement of polishing tool influence functions for edge control. JEOS:RP 6:11048.

  19. Wan S, Zhang X, Zhang H, Xu M, Jiang X (2018) Modeling and analysis of sub-aperture tool influence functions for polishing curved surfaces. Precis Eng 51:415–425

    Article  Google Scholar 

  20. Ren L, Zhang G, Zhang L, Zhang Z, Huang Y (2019) Modelling and investigation of material removal profile for computer controlled ultra-precision polishing. Precis Eng 55:144–153

    Article  Google Scholar 

  21. Walker DD, Baldwin A, Evans R, Freeman R, Wei X, Yu G (2007) A quantitative comparison of three grolishing techniques for the Precessions process. Proc SPIE 6671:66711H

    Article  Google Scholar 

  22. Yu G, Reynolds C, Walker D, Fahnle O (2019) Study of footprint variations of CCP considering machine kinematics. EPJ Web Conf 215(24):05004

    Article  CAS  Google Scholar 

  23. A. Beaucamp, A. Matsumoto, Y. Namba (2010) Ultra-precision polishing by fluid jet and bonnet polishing for next generation hard X-ray telescope application. Proceedings–ASPE 2010 Annual Meeting 3184.

  24. Civitani MM, Parodi G, Vecchi G, Ghigo M, Basso S, Davis JM, Elsner RF, Kiranmayee K, Pareschi G, Swartz D, Toso G (2019) Lynx x-ray optics based on thin monolithic shells: design and development. J Astronomical Telescopes, Instruments, Systems 5(2):021014

    Article  ADS  Google Scholar 

  25. Cheung CF, Lee WB (2001) Characterisation of nanosurface generation in single-point diamond turning. Int J Mach Tool Manuf 41(6):851–875

    Article  Google Scholar 

  26. Goel S, Luo X, Reuben RL (2012) Molecular dynamics simulation model for the quantitative assessment of tool wear during single point diamond turning of cubic silicon carbide. Comput Mater Sci 51(1):402–408

    Article  CAS  Google Scholar 

  27. Tauhiduzzaman M, Veldhuis SC (2014) Effect of material microstructure and tool geometry on surface generation in single point diamond turning. Precis Eng 38(3):481–491

    Article  Google Scholar 

  28. Fan P, Katiyar NK, Goel S, He Y, Geng Y, Yan Y, Mao H, Luo X (2023) Oblique nanomachining of gallium arsenide explained using AFM experiments and MD simulations. J Manuf Processes 90:125–138

    Article  Google Scholar 

  29. Vernani D, Borghi G, Calegari G, Castelnuovo M, Citterio O, Ferrario I, Grisoni G, Moretti S, Valsecchi G, Brauninger H, Burwitz V, Eder J, Friedrich P, Predehl P (2011) Performance of a mirror shell replicated from a new flight quality mandrel for eROSITA mission. Proc SPIE 8147:814707

    Article  Google Scholar 

  30. Beaucamp A, Freeman R, Morton R, Ponudurai K, Walker DD (2008) Removal of diamond-turning signatures on x-ray mandrels and metal optics by fluid-jet polishing. Proc SPIE 7018:701835

    Article  Google Scholar 

  31. Dumas P, Golini D, Tricard M (2005) Improvement of figure and finish of diamond turned surfaces with magneto-rheological finishing (MRF). SPIE, Proc, p 5786

    Google Scholar 

  32. Harvey JE, Thompson AK (1995) Scattering effects from residual optical fabrication errors. Proc SPIE 2576:155–174

    Article  ADS  Google Scholar 

  33. Wang C, Cheng K, Rakowski R, Soulard J (2018) An experimental investigation on ultra-precision instrumented smart aerostatic bearing spindle applied to high speed micro-drilling. J Manuf Processes 31:324–335

    Article  Google Scholar 

  34. Shang Y, Cheng K, Ding H, Chen S (2022) Design and optimization of the surface texture at the hydrostatic bearing and the spindle for high precision machining. Machines 10(9):806

    Article  Google Scholar 

  35. Su X, Ji P, Jin Y, Li D, Walker D, Yu G, Li H, Wang B (2019) Simulation and experimental study on form-preserving capability of bonnet polishing for complex freeform surfaces. Precis Eng 60:54–62

    Article  Google Scholar 

  36. Khaghani A, Cheng K (2020) Investigation on an innovative approach for clamping contact lens mould inserts in ultraprecision machining using an adaptive precision chuck and its application perspectives. Int J Adv Manuf Technol 111:839–850

    Article  Google Scholar 

Download references

Funding

This research was funded by the Key Laboratory of Advanced Manufacturing by Intelligent Technology of the Ministry of Education.

Author information

Authors and Affiliations

  1. School of Mechanical and Power Engineering, Harbin University of Science and Technology, 52 XueFu Road, Harbin, 150080, People’s Republic of China

    YuHao Li & Guo Li

  2. Center for Precision Engineering, Harbin Institute of Technology, 92 West Dazhi Street, Nan Gang District, Harbin, 150001, People’s Republic of China

    JiaDai Xue, Fei Ding & Bo Wang

Authors
  1. YuHao Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guo Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. JiaDai Xue
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fei Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Bo Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors contributed in all tasks during the research process and the writing of this paper.

Corresponding authors

Correspondence to Guo Li or Bo Wang.

Ethics declarations

Ethics approval

Not applicable.

Consent to participate

I agree to participate.

Consent for publication

I agree to publish.

Competing interests

The authors declare no competing interests.

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 (e.g. a society or other partner) 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.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, Y., Li, G., Xue, J. et al. Mechanism of a deterministic sponge figuring processing (SFP) in Ni–P surface formation considering the robustness of the tool influence function: modeling and experimental investigation. Int J Adv Manuf Technol 130, 5563–5589 (2024). https://doi.org/10.1007/s00170-024-13008-w

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00170-024-13008-w

Keywords

Search

Navigation