Improved estimation of the lower percentiles of material properties

Abstract

Estimating lower percentiles in reliability for medium-density fiberboard is an important issue for manufacturers for better assessing and improving manufacturing processes, plus for guiding better product warranties while seeking lower costs. Since data may be sparse or costly in the lower tails, estimation of these percentiles may be difficult. Bootstrapping provides a helpful solution for interval estimation of lower percentiles when other approaches fail or are not as realistic. This computer intensive resampling technique estimates more accurately the true standard error of any population parameter, not just percentiles. Bootstrapping can be used for parametric models or indeed nonparametric settings when parametric models are not appropriate. This paper shows the usefulness of bootstrap methods to better assess the key quality metric of internal bond (IB or tensile strength) of medium-density fiberboard (MDF) in the critical lower percentiles when data are limited.