Incorporating skew into RMS surface roughness probability distributions

Mark T. Stahl; H. Philip Stahl

doi:10.1117/12.2024883

7 September 2013 Incorporating skew into RMS surface roughness probability distributions

Mark T. Stahl, H. Philip Stahl

Proceedings Volume 8838, Optical Manufacturing and Testing X; 883814 (2013) https://doi.org/10.1117/12.2024883
Event: SPIE Optical Engineering + Applications, 2013, San Diego, California, United States

Abstract

Characterizing surface roughness is important for predicting optical performance. Typically, this is accomplished by taking multiple statistically independent measurements and averaging. But, this approach assumes that the statistical distribution of the roughness has a Gaussian (normal) probability distribution. Our analysis shows that this assumption is wrong. Real data acquired from two different sets of telescope optics indicates that roughness of highly polished surfaces is skewed and is best described by a largest extreme value probability (LEV) distribution. Assuming a normal distribution and simply averaging overestimates the most probable surface roughness and could result in the expenditure of unnecessary polishing effort.

Citation Download Citation

Mark T. Stahl and H. Philip Stahl "Incorporating skew into RMS surface roughness probability distributions", Proc. SPIE 8838, Optical Manufacturing and Testing X, 883814 (7 September 2013); https://doi.org/10.1117/12.2024883

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