DESIGNING AN ATTRIBUTE CONTROL CHART BASED ON EXPONENTIAL-RAYLEIGH DISTRIBUTION UNDER HYBRID CENSORING

Statistical Process Control (SPC) is an approach to quality assurance that leverages statistical tools to analyse, monitor, and enhance processes. A control chart is an essential tool for observing process performance; it provides a visual mechanism to identify significant deviations caused by assignable factors. This chart compares the values of a quality attribute against specified control limits. Statistical distributions play a crucial role in parametric inferences and are commonly utilized to characterize real-world phenomena. Researchers have directed their attention towards the advancement of these widely used distributions to generate models that are progressively more realistic and versatile for data interpretation. The new Exponential-Rayleigh distribution can be derived by combining the cumulative distribution functions of both the Exponential and Rayleigh distributions. In this paper, we present a new attribute np control chart aimed at monitoring the median lifetime of products within a hybrid censoring scheme, based on the premise that the lifetimes of these products follow an Exponential-Rayleigh distribution. We determine the optimal parameters for the construction of the proposed control chart to achieve an average run length for the in-control process that is as near as possible to the designated average run length. Various sets of values are utilized to estimate the parameters of the control chart, and the performance of the developed control chart is analyzed through the average run length. Numerical examples are presented to illustrate the proposed control chart, and its applicability is validated with simulated data.