Proper choice of location cumulative sum control charts for different environments

In the field of quality control, statistical process control (SPC) has its significance. The control charts are important tools of the SPC to observe the outputs of the production process. The cumulative sum (CUSUM) charting structure is one such technique that is designed to identify the medium and slight changes in the process parameters. In the literature, the assumption of normality is considered ideal for the control chart but in practice, many quality characteristics do not follow the assumption of normality. The current study proposes a class of CUSUM control charts for the location parameter of the process and investigates the performance of said location charts based on ranked set sampling (RSS) for quality characteristics having different environments. Different point estimators of location are considered in this study to develop the location control charts under normal, and a variety of non-normal environments. The numerical results show that the newly designed schemes perform uniformly well than their competitors. A real-life example linked with the manufacturing process is also provided for the practical implementation of the proposed scheme.