Abstract
Existing variance control charts are designed under the assumptions that no uncertain, fuzzy and imprecise observations or parameters are in the population or the sample. Neutrosophic statistics, which is the extension of classical statistics, has been widely used when there is uncertainty in the data. In this paper, we will originally design S 2 control chart under the neutrosophic interval methods. The complete structure of the neutrosophic S 2 control chart will be given. The necessary measures of neutrosophic S 2 will be given. The neutrosophic coefficient of S 2 control chart will be determined through the neutrosophic algorithm. Some tables are given for practical use. The efficiency of the proposed control chart is shown over the S 2 control chart designed under the classical statistics in neutrosophic average run length (NARL). A real example is also added to illustrate the proposed control chart. From the comparison in the simulation study and case study, it is concluded that the proposed control chart performs better than the existing control chart under uncertainty.
Highlights
In this modern era, the customers demand high-quality products or services to fulfill their needs
We presented the designing of S2 control chart under the neutrosophic interval statistical method
Some necessary measures to assess the performance of the proposed control chart are given
Summary
The customers demand high-quality products or services to fulfill their needs. High quality in a product can be only achieved if the manufacturing process meets the given specifications limits. To the manufacturer to produce the defect-free product, the variation in the process should be controlled. The manufacturing process moves away from control limits due to two types of variation, which are called the natural variation and special variation. To produce the high-quality product that meets the given standard the elimination of variation is necessary. The control chart is one of the important tools that have been widely used in the industry for the monitoring of the process. The control chart immediately informs the engineers if any problem occurs that can shift the process from its target. It is preferable to monitor the process dispersion before the location of the process”. The Shewhart [2] S2 control chart is easy to apply in the industry
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