Approximately Unbiased Estimator for Non-Normal Process Capability Index C-Npk

Abstract

Process capability indices (PCIs) have been extensively used to evaluate and measure whether the process meets the specifications and they provide quality assurance and guide a principal for quality improvement. The index C-pk is the most popular index and is widely used in the manufacturing industry for manufacturing yield evaluation. However, typical evaluations of C-pk depend heavily on the assumption of normal variability. When the underlying distributions are non-normal, the capability evaluations are highly unreliable. In the paper, we apply four various bootstrap methods to construct lower confidence bounds of C-Npk for non-normal processes. We also propose an approximately unbiased estimator of C-Npk for the non-normal processes. Comparisons among the four bootstrap methods with different estimators are provided.