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Multiple dependent states repetitive sampling control chart for monitoring rayleigh distributed data
(Springer, 2022) Gadde, Srinivasa Rao; Adeoti, Olatunde Adebayo
An attribute control chart for Rayleigh distribution based on the multiple dependent state repetitive sampling (MDSRS) is developed in this paper. The performance of the proposed chart is evaluated in terms of average run length for the design of the proposed chart. Furthermore, the control chart constants for instance test time multiplier; inner and outer control limits coefficients are determined by considering the process in-control average run length (ARL) in support of different sample sizes. The efficiency of the proposed chart is compared with some competing control charts using other sampling methods such as single sampling (SS), multiple dependent states (MDS) and repetitive sampling (RS). The application of the proposed chart is illustrated using simulated data, which showed the superiority of the proposed chart as compared to the competing charts. Based on the ARL performance of the proposed chart and the application example, it is recommended that the process engineers use the proposed chart when monitoring the number of failed products that follow the Rayleigh distribution.