Optimization Of Exponentially Weighted Moving Average Statistics Using Empirical Bayesian Weighting Factor

  • J. Ademola J. Adewara Distance Learning Institute, University of Lagos, Akoka, Lagos, Nigeria
  • Ahamefula ,U. Mbata Departments of Mathematics, University of Lagos, Akoka, Lagos, Nigeria

Abstract

The Quality control managers are faced with the challenge of detecting out of control during production which may be assignable or common causes. To monitor and get quality product there is need for the use of Statistical Process Control. The study used EB models for estimating EWMA statistic weighting factor. This is applied to data collected from a tyre producing Company on the weight of radial car tyre of sizes 185, rim 14 Elite. A random sample of size 30 containing five subgroups was taken. The simulalation was done using MCMC of 10000 samples. The result shows that the Uniform-Bernoulli EB model provided a better smooth compared with the Beta-Bernoulli model. In addition, EB models are more reliable in plotting EWMA quality control charts compared with the classical approach.The study further obtained the values for ? in the two EB models as 0.493 ? ? ? 0.506 for Beta-Bernoulli model while Uniform-Bernoulli model is 0.494 ? ? ? 0.506.

Published
2018-04-10
How to Cite
Adewara, J. A. J., & Mbata, A. ,U. (2018). Optimization Of Exponentially Weighted Moving Average Statistics Using Empirical Bayesian Weighting Factor. International Journal of Mathematical Sciences and Optimization: Theory and Applications, 2016, 83 - 94. Retrieved from http://ijmso.unilag.edu.ng/article/view/21
Issue
Vol 2016 (2016)
Section
Articles

This is an Open Access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, adaptation, and reproduction in any medium, provided that the original work is properly cited.