Multivariate Process Capability Index: A Review and Some Results

Das Nandini () and Dwivedi Prem Saurav
Additional contact information
Das Nandini: SQC & OR Unit, Indian Statistical Institute, 203 B T Road, Kolkata-700108, India
Dwivedi Prem Saurav: SQC & OR Unit, Indian Statistical Institute, 203 B T Road, Kolkata-700108, India

Stochastics and Quality Control, 2013, vol. 28, issue 2, 151-166

Abstract: Process capability is defined as inherent variability of a process which is running under chance cause of variation only. Process capability index is measuring the ability of a process to meet the product specification limit. Generally Cp and Cpk have been widely used as statistical tools to assess the manufacturing process performance. These indices provide numerical measures on process precision, process accuracy and process performance. The multivariate process capability indices, which are used for evaluation of processes with correlated quality characteristics are considered as new emerging research area. In this paper, we describe an approach of estimating multivariate process capability indices assuming multivariate g-and-h distribution and illustrate their performance using simulated and practical data set.

Keywords: Multivariate g-and-h Distribution; Multivariate Quantile; Non-Normal Distribution; Multivariate g-and-h Distribution; Multivariate Quantile; Non-Normal Distribution (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/eqc-2013-0022 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bpj:ecqcon:v:28:y:2013:i:2:p:16:n:9

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/eqc/html

DOI: 10.1515/eqc-2013-0022

Access Statistics for this article

Stochastics and Quality Control is currently edited by George P. Yanev

More articles in Stochastics and Quality Control from De Gruyter
Bibliographic data for series maintained by Peter Golla ().