Research Article Open Access

Confidence Interval for Cpm Based on Dp,q Distance

Bahram Sadeghpour Gildeh and Samaneh Asghari

Abstract

Problem statement: A measurement control system ensures that measuring equipment and measurement processes are fit for their intended use and its importance in achieving product quality objectives. Approach: The manufacturing industries have been making an extensive effort to implement Statistical Process Control (SPC) in their plants and supply bases. Results: Capability indices derived from SPC have received increasing usage not only in capability assessments, but also in the evaluation of purchasing decisions. In most real life applications, real observations of continuous quantities are not precise numbers; in practice, they are more or less imprecise. Since observations of continuous random variables are imprecise the values of related test statistics become imprecise. In some cases Specification Limits (SLs) are not precise numbers and they are expressed in fuzzy terms, so that the classical capability indices could not be applied. Conclusion/Recommendations: In this study we obtain 100(1-α)% fuzzy confidence interval for Cpm fuzzy process capability index, where instead of precise quality we have two membership functions for specification limits.

Journal of Mathematics and Statistics
Volume 8 No. 1, 2012, 114-121

DOI: https://doi.org/10.3844/jmssp.2012.114.121

Submitted On: 4 June 2011 Published On: 8 February 2012

How to Cite: Gildeh, B. S. & Asghari, S. (2012). Confidence Interval for Cpm Based on Dp,q Distance. Journal of Mathematics and Statistics, 8(1), 114-121. https://doi.org/10.3844/jmssp.2012.114.121

  • 4,101 Views
  • 2,576 Downloads
  • 4 Citations

Download

Keywords

  • Fuzzy set
  • membership function
  • process capability index
  • triangular fuzzy number
  • fuzzy random variable