Abstract
ABSTRACTIn statistical process control applications, profiles functions are considered an efficient way of representing quality of products or processes. Classical and Bayesian thoughts are two chief sources of defining control charting structures for profiles monitoring. This Study introduces novel Bayesian CUSUM control structures for profiles monitoring. The comprehensive comparative study identifies that the proposed Bayesian CUSUM control charts under conjugate priors has better expected performance than competing methods. The implementation of Bayesian structures requires detailed information about process parameters which come up with considerable benefits. In addition, simulative example and case study further justified the superiority of proposed techniques.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Communications in Statistics - Simulation and Computation
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
