Generalized Process Capability Index and its Statistical Inference

The present book, define generalized process capability index (GPCI) which could be used for more general purposes and could be used for continuous (normal and non-normal both) as well as discrete quality characteristic. Even it would be good if unilateral as well as bilateral specifications are to be considered also. The estimate of GPCI possesses good distributional and statistical properties. The proposed GPCI is defined as the ratio of proportion of specification conformance to proportion of desired conformance. The GPCI overcomes many deficiencies of the standard PCIs and all most all the PCIs defined in the literature are directly or indirectly associated with it. At the same time it would be user friendly i.e., easy and comprehensive to practitioners as well as to scientists. The maximum likelihood estimator (MLE), the minimum variance unbiased estimator (MVUE) and the lower confidence limits connected to this index is to be studied. When there are some prior information, Bayes estimate and its credible interval are to be studied. A curve fitting method is to be proposed and to be compared with other standard curve fitting methods.

Autorentext

Mahendra Saha is working as an Assist. Prof. in Dept. of Statistics, CURAJ, from March, 2013. His research interest is on Industrial & Actuarial Statistics, Lifetime Data Analysis .Sudhansu S. Maiti is working as a Prof. in Dept. of Statistics, Visva-Bharati, from March, 2013. His research interest is on Industrial Statistics, Distribution Theory