Title: A process capability index for mixed binary-normal quality characteristics

Authors: Amirhossein Amiri; Ehsan Bahrami Samani; Hamed Mogouie; Mohammad Hadi Doroudyan; Mohammad Hadi Doroudyan

Addresses: Industrial Engineering Department, Faculty of Engineering, Shahed University, Khalije Fars high way, Tehran, P.O. Box 18151-159, Iran ' Department of Statistics, Faculty of Mathematical Science, Shahid Beheshti University, Tehran, 1983963113, Iran ' Industrial Engineering Department, Faculty of Engineering, Shahed University, Khalije Fars high way, Tehran, P.O. Box 18151-159, Iran ' Industrial Engineering Department, Faculty of Engineering, Yazd university, Yazd, Iran ' Industrial Engineering Department, Faculty of Engineering, Yazd University, Yazd, P.O. Box 89195-741, Iran

Abstract: While most of the methods developed for computing process capability indices (PCI) concentrate on cases with normally or continuous non-normally distributed quality characteristics, computing this measure for processes with mixed distributed data has not been investigated so far. In this paper, a new method is proposed for computing (PCI) for mixed binary-normal quality characteristics. In the proposed method, first a mixed binary-normal distribution is considered to be fitted on the available data. Having estimated the unknown parameters of the fitted distribution using maximum likelihood estimation and genetic algorithm, the proportion of the conforming items of the corresponding distribution is estimated by Monte Carlo simulation runs. Finally, the PCI is computed based on the relationship of PCI and proportion of conforming items. The performance of the proposed method is evaluated using simulation studies as well as a case study in a plastic injection moulding process.

Keywords: process capability index; PCI; mixed binary normal quality characteristics; conforming items; maximum likelihood estimation; MLE; genetic algorithms; GAs; plastic injection moulding; Monte Carlo simulation.

DOI: 10.1504/IJQET.2014.059846

International Journal of Quality Engineering and Technology, 2014 Vol.4 No.1, pp.66 - 80

Received: 11 May 2013
Accepted: 29 Jul 2013
Published online: 17 May 2014 *

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