Avaliação do desempenho do gráfico de controle S^2 para variância com uso da regra suplementar de 2-2 de Klein por meio de simulação de Monte Carlo

Abstract

Every production process or service provision has a certain variability in its characteristic of interest. However, the variability can be altered by special causes not inherent in the process and thus need to be eliminated as quickly as possible. In this sense, the use of Statistical Process Control (SPC) techniques are essential for the rapid detection of change in variability. In particular, the S^2 control chart is an important tool to detect changes in variability. However, it is known that the S^2 control chart does not perform well for small variance shifts. Therefore, the purpose of this study is to analyze the performance of the control chart S^2 using Klein's supplementary rule, in which the process can be considered as out of control when two sequential points are above the upper control limit or below the lower control limit. The results obtained in the work indicate that for small displacements in the variance, the use of the control chart using the rule proposed by Klein is more efficient, as it presents a lower Average Run Lengths (ARL) for small displacements compared to the use of the traditional chart.