Find in Library

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 <inline-formula> <math display="inline"> <semantics> <mrow> <msup> <mi>S</mi> <mn>2</mn> </msup> </mrow> </semantics> </math> </inline-formula> control chart under the neutrosophic interval methods. The complete structure of the neutrosophic <inline-formula> <math display="inline"> <semantics> <mrow> <msup> <mi>S</mi> <mn>2</mn> </msup> </mrow> </semantics> </math> </inline-formula> control chart will be given. The necessary measures of neutrosophic <inline-formula> <math display="inline"> <semantics> <mrow> <msup> <mi>S</mi> <mn>2</mn> </msup> </mrow> </semantics> </math> </inline-formula> will be given. The neutrosophic coefficient of <inline-formula> <math display="inline"> <semantics> <mrow> <msup> <mi>S</mi> <mn>2</mn> </msup> </mrow> </semantics> </math> </inline-formula> 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 <inline-formula> <math display="inline"> <semantics> <mrow> <msup> <mi>S</mi> <mn>2</mn> </msup> </mrow> </semantics> </math> </inline-formula> 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.