This paper evaluates the performance of process capability indices, PCI in non-normal situations percentiles using the methods of Clements (CCP CCpk) and Burr (BCP BCpk). Although the PCI is used in industry, there is insuffi cient literature to determine their accuracy by taking into account moderate and severe deviations of the normality. To study these deviations, it performs a comparison of both methods considering simulated data distributions with the Weibull, Lognormal, Beta and Generalized Pareto, GP. In calculating the PCI the CCpk generates smaller deviations with the Weibull distribution, whereas that the BCpk, deviations are higher. On the other side with each distribution the BCP generates lower average deviation from the CCP. Finally a real case considering the distribution GP.

This paper evaluates the performance of process capability indices, PCI in non-normal situations percentiles using the methods of Clements (CCP CCpk) and Burr (BCP BCpk). Although the PCI is used in industry, there is insuffi cient literature to determine their accuracy by taking into account moderate and severe deviations of the normality. To study these deviations, it performs a comparison of both methods considering simulated data distributions with the Weibull, Lognormal, Beta and Generalized Pareto, GP. In calculating the PCI the CCpk generates smaller deviations with the Weibull distribution, whereas that the BCpk, deviations are higher. On the other side with each distribution the BCP generates lower average deviation from the CCP. Finally a real case considering the distribution GP.