International Journal of Management and Applied Science (IJMAS)
current issues
Volume-5,Issue-1  ( Jan, 2019 )
Past issues
  1. Volume-5,Issue-1  ( Jan, 2019 )
  2. Volume-4,Issue-12  ( Dec, 2018 )
  3. Volume-4,Issue-11  ( Nov, 2018 )
  4. Volume-4,Issue-10  ( Oct, 2018 )
  5. Volume-4,Issue-9  ( Sep, 2018 )
  6. Volume-4,Issue-8  ( Aug, 2018 )
  7. Volume-4,Issue-7  ( Jul, 2018 )
  8. Volume-4,Issue-6  ( Jun, 2018 )
  9. Volume-4,Issue-5  ( May, 2018 )
  10. Volume-4,Issue-4  ( Apr, 2018 )

Statistics report
Mar. 2019
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 59
Paper Published : 3874
No. of Authors : 7966
  Journal Paper




Paper Title :
Testing Weibull Process Yield using The Markov Chain Monte Carlo Method

Author :Mou-Yuan Liao

Article Citation :Mou-Yuan Liao , (2018 ) " Testing Weibull Process Yield using The Markov Chain Monte Carlo Method " , International Journal of Management and Applied Science (IJMAS) , pp. 13-15, Volume-4,Issue-10

Abstract : Process capability index pk C is a popular index used to make managerial decisions on quality assurance because it provides bounds on the process yield of a normally distributed process. However, the normality assumption is often invalid, so it has become challenging for quality managers to accurately assess pk C values. In this study, we provide an alternative method for assessing the pk C value of a non-normal process. The Markov chain Monte Carlo method was integrated into a Bayesian model and adapted to determine the empirical posterior distributions of pk C and thereby obtain the credible intervals for testing pk C . Keywords - Bayesian; Markov chain Monte Carlo; Process capability.

Type : Research paper


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