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Latent Image Sample Processing Using Machining Center

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Abstract

We have proposed latent image processing using a machining center, and have been conducting research in our laboratory for several years. Consequently, at present, the processing method is almost established, and it has become possible to process samples that are reasonably satisfactory in terms of cost and processing quality. However, currently, the evaluation method of latent image processing quality relies on visual inspection. Moreover, from the beginning, we believed that latent image processing could be used to make souvenirs and during experimental training at educational institutions, such as our institute, but until now, we had not specifically considered how to use it. Therefore, in this paper, we first introduce the three types of latent image processing that have been performed thus far, and summarize their characteristics. Subsequently, the evaluation method of the latent image processing quality and the utilization method are newly examined and the result of the confirmation is reported.

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References

  1. Takeuchi, Y., Sawada, K., & Sata, T. (1996). Ultraprecision 3D micromachining of glass. CIRP Annals, 45(1), 401–404.

    Article  Google Scholar 

  2. Takino, H., Kawai, T., & Takeuchi, Y. (2007). 5-axis control ultra-precision machining of complex-shaped mirrors for extreme ultraviolet lithography system. CIRP Annals, 56(1), 123–126.

    Article  Google Scholar 

  3. Sato, R., et al. (2019). Improvement of simultaneous 5-axis controlled machining accuracy by CL-data modification. International Journal of Automation Technology, 13(5), 583–592.

    Article  Google Scholar 

  4. Jung, S.-T., et al. (2020). Research on ultra-precision fine-pattern machining through single crystal diamond tool fabrication technology. Journal of the Korea Society of Die & Mold Engineering, 14(3), 63–70.

    Google Scholar 

  5. Hwang, J.-D., & Yun, I.-W. (2020). 5-axis machining of impellers using geometric shape information and a vector net. Journal of the Korean Society of Manufacturing Process Engineers, 19(3), 63–70.

    Article  MathSciNet  Google Scholar 

  6. Li, D., Zhang, W., Zhou, W., et al. (2018). Dual NURBS path smoothing for 5-axis linear path of flank milling. International Journal of Precision Engineering and Manufacturing, 19, 1811–1820.

    Article  Google Scholar 

  7. Ma, J., Ma, F., Wang, Z., et al. (2022). Effect of ball end cutter tilt milling on path interval of blade surface. International Journal of Precision Engineering and Manufacturing, 23, 1211–1223.

    Google Scholar 

  8. Ishihara, K. (2003). Japan money collected encyclopedia. Gentensya (p. 266).

  9. Kanzaki, Y., Minotsukuri, K., & Utsuno, Y. (2009). Publication patent application, Japan Patent Office, P2009-189479A.

  10. Aritomi, M. (2007). Information processing apparatus, method, and program for selecting dynamic information with high priority for latent image printing. U.S.Patent 8441693B2.

  11. Uchida, T., et al. (2003). Image processing apparatus and image processing method for distinguishing between an original print product and a copy of the print product. U.S.Patent 7274890B2.

  12. Nakata, H., et al. (2005). Image processing apparatus and a control method for forming forgery-inhibited pattern images. U.S.Patent 7999973B2.

  13. Mann, M., Shukla, S., & Gupta, S. (2015). A comparative study on security features of banknotes of various countries. International Journal of Multidisciplinary Research and Development, 2, 83–91.

    Google Scholar 

  14. Ihara, M., Yamaji, I., & Matsubara, A. (2022). Quantitative evaluation of machined-surface gloss using visual simulation and its application to sensory test. International Journal of Automation Technology, 16(2), 167–174.

    Article  Google Scholar 

  15. Minami, M., et al. (2006). Finding and quantitative evaluation of minute bruise on metal surface using hairline. Transactions of the Japan Society of Mechanical Engineers Part C, 72(7), 2240–2247.

    Article  Google Scholar 

  16. Kato, K., Ioi, T., & Enomoto, S. (2007). Study on visual evaluation for barrel finished surfaces. Transactions of the Japan Society of Mechanical Engineers Part C, 73(4), 1202–1207.

    Article  Google Scholar 

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Acknowledgements

This study was partly supported by the Mazak Foundation, and we wish to express our gratitude.

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Correspondence to Toru Yamamoto.

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Yamamoto, T., Kunimune, R. Latent Image Sample Processing Using Machining Center. Int. J. Precis. Eng. Manuf. 24, 1253–1262 (2023). https://doi.org/10.1007/s12541-023-00810-x

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  • DOI: https://doi.org/10.1007/s12541-023-00810-x

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