Abstract
This paper proposes a new distribution-free control chart by integrating the powerful nonparametric two-sample Cramér-von Mises test and the exponentially weighted moving average control scheme to on-line monitoring. The proposed control chart can be used to monitor the location and the scale parameters of a univariate continuous distribution, simultaneously. The control limits based on Monte-Carlo simulation are provided in a table. The sensitivity analysis of effect of the number of reference samples on the control chart is studied in detail. Comparison results based on Monte-Carlo simulation show that the proposed chart is quite robust to non-normally distributed data, and moreover, it shows satisfactory performance in detecting various process shifts in terms of the average run length and standard deviation of run length. The application of our proposed chart is illustrated by a real data example for automobile engine piston rings.
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.
