Form error estimation is an essential step in the assessment of product geometry created through one or more manufacturing processes. We present a new method using spatial statistics to estimate form error. Using large sets of uniform sample points measured from five common machined surfaces, we compare the form error estimates using individual points and fitted surfaces obtained through spatial statistical methods. The results show that spatial statistics can provide more accurate estimates of form error under certain conditions. Disciplines Industrial Engineering | Statistics and Probability | Systems Engineering CommentsThis is an article from Transactions of the ASME 262 (2000)

Form error estimation techniques based on discrete point measurements can lead to significant errors in form tolerance evaluation. By modeling surface profiles as random variables, we show how sample size and fitting techniques affect form error estimation. Depending on the surface characteristics, typical sampling techniques can result in estimation errors of as much as 50 percent. Another issue raised in the fitting approach is the metric p selection for the fitting objective. We show that for p = 2 and p = ∞, the selection does not appear to significantly affect the estimation of form errors

Form error estimation is a critical step in verifying that a product satis®es design speci®cations. It is demonstrated how Shannon sampling can be used to reconstruct surface pro®les if they are treated as band-limited signals. To demonstrate its use in form estimation, a Shannon sampling series is applied to¯atness error estimation for uniform sample points measured from ®ve common machined surfaces. The results indicate that Shannon sampling provides superior performance over using points directly for estimation.

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