Multivariate Hotelling-T2 Control Chart for Neutrosophic Data

Abstract

Industries are consistently confronted with a myriad of challenges, the most significant of which is the requirement to increase product quality while simultaneously minimising manufacturing costs. Statistical Process Control (SPC) provides quality control charts as one of its primary methods for achieving this goal. When it comes to monitoring the quality features of a process, the control chart is the most popular and widely used kind of statistical analysis tool. It is very necessary to make use of multivariate control charts if the quality of a process is found to be connected with more than one characteristic. The Hotelling-T2 chart is one of the most familiar methods of multivariate control chart. It is used for simultaneously monitoring the process mean and determining whether or not the process mean vector for two or more variables is under control. However, this is applicable only when the data is accurate, determined, and exact. As a result, when the data is vague or ambiguous, the utility of the conventional Hotelling-T2 control chart is limited. Within the scope of this research, we put up a neutrosophic Hotelling-T2 control chart as a potential solution to the issue described above. The performance of the proposed chart is evaluated using simulation at various degrees of shift in process average, with the neutrosophic alarm rate serving as the performance measure. To further investigate the applicability of the sug-gested chart in the actual world, we made use of a real-world example taken from the chemical sector.