Neutrosophic Rayleigh Model With Some Basic Characteristics and Engineering Applications

Abstract

The fundamentals of neutrosophic statistics provide a new basis for working with indeterminate data problems. In this study, the notion of the neutrosophic Rayleigh distribution (RDN) has been introduced. The neutrosphic extension of the classical Rayleigh model with several application areas is highlighted. The major characteristics of the proposed distribution are described in a way that suggested model can be utilized in different situations involving undetermined, vague and fuzzy data. The usage of proposed distribution notably in the domain of statistical process control (SPC) is considered. The classical structure of V-SQR-chart is not capable of capturing uncertainty on studied variables. The mathematical structure of the V-NR-chart based on the proposed neutrosophic distribution has been developed. The neutrosphic parameters of the proposed V-NR-chart with other related performance metrics such as neutrosophy run length (ARL(N)) and neutrosophy power curve (PCN) are established. The proposed chart's performance in a neutrosophic environment is also evaluated to the existing model. Results from this comparative analysis reveal that the suggested V-NR-chart outperforms its current equivalent in terms of neutrosophic statistical power. Finally, a charting structure of proposed design for service life of ball bearings data is considered with a view to support implementation procedure of the proposed neutrosophic design in real-world scenarios.