Neutrosophic Rayleigh Model With Some Basic Characteristics and Engineering Applications

Zahid Khan,Nasreen Kausar,Choonkil Park,Muhammad Gulistan

doi:10.1109/access.2021.3078150

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 (RD N ) 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 (PC N ) 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.

Highlights

Variability is an inevitable phenomenon of the production industry
By changing the neutrosophic target parameter to σ, the performance of the V -chart in terms of power curve (PC) function can be evaluated for different values of m and α
The classical Rayleigh model has been extended in accordance with neutrosophic logic

Summary

INTRODUCTION

Variability is an inevitable phenomenon of the production industry. It is often due to normal causes and specific causes of variation. The SPC is a common technique that involves statistical tools to precisely measure variations in the parameters of the production or manufacturing process [2]. A statistical quality control chart, an effective technique in the SPC, is commonly practiced in service and manufacturing industries to analyze the behavior of processes in addition to enhancing their productivity [3]. For applications containing imprecise data are handled by different researchers using the neutrosophic statistics (NST) [14]–[16]. The classical approach of the conventional statistical techniques has been generalized in the area of NST with the purpose to deal with vagueness in processing data. The V is one of such designs to accommodate this non-normality situation for quality data that best described by the classical Rayleigh model [23].

Neutrosophic Rayleigh Model Definition

Performance Analysis

Comparison Analysis

REAL APPLICATION

CONCLUSION