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Adaptive neuro fuzzy determination of impactful factors on non-uniformity of polished surface

Dalibor Petkovic

Corresponding Author:

Dalibor Petkovic

Affiliation(s):

University of Niš, Pedagogical Faculty in Vranje, Partizanska 14, 17500 Vranje, Serbia
Email: [email protected]

Abstract:

In this study, the neuro fuzzy logic selection of the most influential parameters for non-uniformity of polished surface was performed. The influence of three parameters was analyzed: carrier load, thickness and the pads elastic modulus. Adaptive neuro fuzzy logic or ANFIS was used for establishing the nonlinear relationships between the three parameters and the non-uniformity polished surface. Dataset for training and testing procedure was extracted by finite element model. According to the regression models, thickness of pad has the greatest influence on the non-uniformity. Moreover, elastic modulus and pad thickness are the optimal combination of non-uniformity. Results could be useful in the improvement of chemical polishing process.

Keywords:

Wafer, Chemical, Polishing Process, Non-uniformity, Neuro Fuzzy

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Cite This Paper:

Dalibor Petkovic (2019). Adaptive neuro fuzzy determination of impactful factors on non-uniformity of polished surface. Journal of the Institute of Electronics and Computer, 1, 9-16. https://doi.org/10.33969/JIEC.2019.11002.

References:

[1] Lu, A., Jin, T., Liu, Q., Guo, Z., Qu, M., Luo, H., & Han, M. (2019). Modeling and prediction of surface topography and surface roughness in dual-axis wheel polishing of optical glass. International Journal of Machine Tools and Manufacture, 137, 13-29
[2] Zhong, G., Ning, Y., Zhou, Q., Bian, Y., Wang, X., Qu, X., ... & Zhao, E. (2017). Influence of pre-polishing process on site flatness values of polished wafers. Materials Science in Semiconductor Processing, 68, 15-20.
[3] Li, L., He, Q., Zheng, M., Ren, Y., & Li, X. (2019). Improvement in polishing effect of silicon wafer due to low-amplitude megasonic vibration assisting chemical-mechanical polishing. Journal of Materials Processing Technology, 263, 330-335
[4] Zhai, K., He, Q., Li, L., & Ren, Y. (2017). Study on chemical mechanical polishing of silicon wafer with megasonic vibration assisted. Ultrasonics, 80, 9-14.
[5] Pandey, K., & Pandey, P. M. (2017). Chemically assisted polishing of monocrystalline silicon wafer Si (100) by DDMAF. Procedia engineering, 184, 178-184.
[6] Chen, C. C. A., Shu, L. S., & Lee, S. R. (2003). Mechano-chemical polishing of silicon wafers. Journal of Materials Processing Technology, 140(1-3), 373-378.
[7] Rao, C., Wang, T., Wang, J., Liu, Y., & Lu, X. (2016). Improvement of via dishing and non-uniformity in TSV chemical mechanical planarization. Microelectronic Engineering, 151, 38-46.
[8] Li, J., Wei, Z., Wang, T., Cheng, J., & He, Q. (2017). A theoretical model incorporating both the nano-scale material removal and wafer global uniformity during planarization process. Thin Solid Films, 636, 240-246
[9] Jang, J.-S.R, ANFIS: Adaptive-Network-based Fuzzy Inference Systems, IEEE Trans. On Systems, Man, and Cybernetics (1993), Vol.23, 665-685.
[10] Lo, S. P., & Lin, Y. Y. (2005). The prediction of wafer surface non-uniformity using FEM and ANFIS in the chemical mechanical polishing process. Journal of Materials Processing Technology, 168(2), 250-257.