New Control Chart Based On Neutrosophic Maxwell Distribution with Decision Making Applications

Abstract

The neutrosophic approach is a potential area to provide a novel framework for dealing
with uncertain data. This study aims to introduce the neutrosophic Maxwell distribution (MD̃ ) for
dealing with imprecise data. The proposed notions are presented in such a manner that the
proposed model may be used in a variety of circumstances involving indeterminate, ambiguous,
and fuzzy data. The suggested distribution is particularly useful in statistical process control (SPC)
for processing uncertain values in data collection. The existing formation of VSQ-chart is incapable of
addressing uncertainty on the quality variables being investigated. The notion of neutrosophic VSQchart (ṼSQ) is developed based on suggested neutrosophic distribution. The parameters of the
suggested ṼSQ-chart and other performance indicators, such as neutrosophic power curve (PC̃),
neutrosophic characteristic curve (CC̃) and neutrosophic run length (RL̃) are established. The
performance of the ṼSQ-chart under uncertain environment is also compared to the performance of
the conventional model. The comparative findings depict that the proposed ṼSQ-chart outperforms
in consideration of neutrosophic indicators. Finally, the implementation procedure for real data on
the COVID-19 incubation period is explored to support the theoretical part of the proposed model.