Browsing Mechanical & Industrial Engineering by Author "Jeong M.K."
Now showing items 1-3 of 3
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Bayesian framework for fault variable identification
Turkoz M.; Kim S.; Jeong Y.-S.; Jeong M.K.; Elsayed E.A.; Al-Khalifa K.N.; Hamouda A.M.... more authors ... less authors ( Taylor and Francis Inc. , 2019 , Article)In most manufacturing processes, identifying the faulty process variables that may lead to process changes is crucial for quality engineers and practitioners. There are several parametric procedures for identifying faulty ... -
Monitoring and control of beta-distributed multistage production processes
Kim, S.; Kim, J.; Jeong, M. K.; Al-Khalifa, K. N.; Hamouda , A. M. S.; Elsayed, E. A.... more authors ... less authors ( Taylor and Francis Ltd. , 2019 , Article)Multistage statistical process control (SPC) is an effective procedure for ensuring quality of products in multistage manufacturing processes. Effective SPC approaches for monitoring and controlling quality in multistage ... -
Multivariate statistical process control charts based on the approximate sequential ?2 test
Kim, J.; Al-Khalifa, K.N.; Jeong, M.K.; Hamouda, A.M.S.; Elsayed, E.A. ( Taylor and Francis Ltd. , 2014 , Article)Similar to the univariate CUSUM chart, a multivariate CUSUM (MCUSUM) chart can be designed to detect a particular size of the mean shift optimally based on the scheme of a sequential likelihood ratio test for the noncentrality ...