The economic design of multivariate binomial EWMA VSSI control charts

Abstract

Since multi-attribute control charts have received little attention compared with multivariate variable control charts, this research is concerned with developing a new methodology to employ the multivariate exponentially weighted moving average (MEWMA) charts for m-attribute binomial processes; the attributes being the number of nonconforming items. Moreover, since the variable sample size and sampling interval (VSSI) MEWMA charts detect small process mean shifts faster than the traditional MEWMA, an economic design of the VSSI MEWMA chart is proposed to obtain the optimum design parameters of the chart. The sample size, the sampling interval, and the warning/action limit coefficients are obtained using a genetic algorithm such that the expected total cost per hour is minimized. At the end, a sensitivity analysis has been carried out to investigate the effects of the cost and the model parameters on the solution of the economic design of the VSSI MEWMA chart.

Engineering applications of organic surfactant modified bentonite in sorptive soil barriers.

“…To obtain the transport parameters of benzene under non-equilibrium condition, two approaches including kinetic study and analytical solutions were employed. The results of retardation factor for non-equilibrium condition showed a good agreement between the calculated results from kinetic study and estimated result from analytical solution (Niaki and Jahani 2012;Niaki and Jahani 2013). This result suggested that the non-equilibrium partitioning coefficient measured from kinetic study can be employed to calculate a reliable retardation factor in non-equilibrium condition.…”

Nonparametric cost‐minimized Shewhart‐type process monitoring with restricted false alarm probability

“…Traditional Duncan‐type economic models determine the optimal design parameters of a monitoring scheme, usually comprising of the sample size (say, n ), sampling interval (say, h ), and control limit (say, l ), based on a specific distributional form for the process characteristic of interest (for example, see Niaki and Jahani, Saghaei et al, Seif et al, Costa and Fichera). In the current article, we present an improved economic model for NSPM schemes which is adapted from Duncan's economic model and consider that the process characteristic follows an unknown continuous univariate distribution.…”

A Multivariate EWMA Control Chart with fuzzy approach for multinomial variables.

“…Although the T 2 control charts have been widely used, they show a decrease in their performance when the shift in the vector of means is small or medium, in this situation a proposal is the Multivariate Exponentially Weighted Moving Average (MEWMA) control chart, developed by [13]. Several versions of MEWMA type charts have been developed for discrete variables: for Poisson variables, there are some works such as those developed by [14] and [15]; while, for binomial variables [16] and for multinomial variables [17].…”