Abstract
An intelligent quality diagnosis method for process quality diagnosis and improvement was proposed to find out influencing input parameters for output quality and then provide suggestion for quality engineering to adjust them to acquire high quality performance. The diagnosis method extends the traditional quality control and diagnosis method that only for the output quality of manufacturing process. It can detect the input parameters of the manufacturing process and provide sensitivities of input parameter for adjustment. BN-MTY method was applied to explain the reason of quality failure in T2 control chart and the root output quality indicators that aroused the process quality anomaly was located. The integrated method of neural network and sensitivity analysis was applied to get the weight and threshold value of neural cell in the forecasting network. his integrated quality diagnosis method can diagnose the input parameters and provide accurate sensitivities for quality improvement.
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 callDisclaimer: 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.
