A new method in selective assembly for components with skewed distributions
S.M. Kannan,
R. Sivasubramanian and
V. Jayabalan
International Journal of Productivity and Quality Management, 2009, vol. 4, issue 5/6, 569-589
Abstract:
A product consists of two or more components assembled together is an assembly. The quality of the product depends upon the quality of the assembly. The contributing quality characteristics of the mating parts play a major role. A good amount of research has been carried out to improve the quality of assembly using selective assembly, when the contributing quality characteristics confirms to normal distribution. However, in reality, the contributing quality characteristics of a component will have some skewness, which will make the models proposed by earlier researcher not suitable for practice. In this paper, a new method is proposed with component quality characteristics having skewness and selective assembly can be effectively used to meet the specification requirements without any surplus parts. The proposed method ensures that all the components of the mating part population is used and at the same time there is minimum variation in the assembly even there is skewness in the dimensional distribution of the mating parts. Genetic algorithm (GA) is used to find the number of components in selective group combinations for a given clearance variation.
Keywords: selective assembly; clearance variation; genetic algorithms; GAs; skewed distribution; assembly quality; component quality. (search for similar items in EconPapers)
Date: 2009
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.inderscience.com/link.php?id=25186 (text/html)
Access to full text is restricted to subscribers.
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:ids:ijpqma:v:4:y:2009:i:5/6:p:569-589
Access Statistics for this article
More articles in International Journal of Productivity and Quality Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().