Monitoring of production of blood components by attribute control chart under indeterminacy

Nasrullah Khan,Muhammad Aslam,S Balamurali,P Jeyadurga

doi:10.1038/s41598-020-79851-5

Abstract

The existing control chart for monitoring the blood components by attribute is designed using classical statistics. The existing attribute control chart can be applied only when the experimenter is sure about the proportion of defective or all the observations in the sample are determined. In this paper, new attribute control charts for monitoring the blood components under the neutrosophic statistics will be presented. The design of the proposed control chart is given under the neutrosophic statistical interval method. The applications of these control charts demonstrate that the proposed control charts are quite effective, adequate, flexible, and informative for monitoring the blood components under uncertain environment.

Highlights

The existing control chart for monitoring the blood components by attribute is designed using classical statistics
One can ensure the consistency of process output by using statistical process control (SPC) techniques in which the product quality is measured during the manufacturing process
Neutrosophic logic seems like fuzzy logic, in neutrosophic logic three cases of membership function are considered such as degree of truth-membership T, degree of falsity membership F and degree of indeterminacy membership I. 18proposed neutrosophic statistical methods to interpret and organize the data which are indeterminate and mentioned that neutrosophic statistics is an extension of classical statistics

Summary

Introduction

The existing control chart for monitoring the blood components by attribute is designed using classical statistics. Variables control charts yield more information about the process and involve a minimum sample size since it utilizes quantitative data. Acceptance sampling plans and control charts are designed under neutrosophic statistics (see, for example, 20,21). 23discussed the construction of attribute control charts using classical statistics, and the status of the process was determined based on constant control limits.

Results

Conclusion