تصفح Mechanical & Industrial Engineering حسب المؤلف "Kim S."
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An adaptive thresholding-based process variability monitoring
Abdella G.M.; Kim J.; Kim S.; Al-Khalifa K.N.; Jeong M.K.M.K.; Hamouda A.M.; Elsayed E.A.... more authors ... less authors ( Taylor and Francis Inc. , 2019 , Article)In high-dimensional processes, monitoring process variability is considerably difficult due to the large number of variables and the limited number of samples. Monitoring changes in the covariance matrix of a multivariate ... -
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 ... -
Control charts for variability monitoring in high-dimensional processes
Kim J.; Abdella G.M.; Kim S.; Al-Khalifa K.N.; Hamouda A.M. ( Elsevier Ltd , 2019 , Article)Monitoring process variability is associated with detecting changes in the covariance matrix of a multivariate normal process. Most monitoring methods estimate the sample covariance matrix and compare it with the in-control ... -
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 ...