Short Title: Int. J. Mech. Eng. Robot. Res.
Frequency: Bimonthly
Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
2024-12-18
2024-10-25
Abstract—Control charts play a very important role in Statistical Process Control. Run sum S control chart is sensitive in detecting small to moderate shifts. It is an excellent alternative to Shewhart control chart. The performance of the run sum S control chart based on median run length (MRL) performance is proposed in this study. The Statistical Analysis System (SAS) program was used to calculate the in-control ARL and in-control MRL for the nine run sum S chart schemes with different sample sizes, magnitude of shift in the process standard deviation, and the in-control run lengths. The findings show that the MRL measure provides better explanation than the ARL criterion. Moreover, the MRL performance of the run sum S chart schemes is substantially affected by the sample sizes, magnitude of shift in the process standard deviation, and the in-control run lengths.