Economic design of a nonparametric EWMA control chart for location

Abstract

In this article, we have proposed an economic design of Exponentially Weighted Moving Average control chart based on sign statistic to control location parameter of the process. The economic performance of the chart is evaluated for different shifts in the location. It is observed that, as shift in the process location increases, sample size to detect the shift and the loss cost from the process decrease. The power of the chart increases with increasing shift. The design gives better economic/statistical performance for large shifts in the process. This economic procedure can be applied to any process having known or unknown process outcome distribution. The sensitivity of the design is also carried out to check the effect on statistical as well as economic performance of the design due to change in different time and cost parameters.

New Integrated Model for Maintenance Planning and Quality Control Policy for Multi-Component System Using an EWMA Chart

“…If the PM for a system is designed using incomplete maintenance, the component failure behavior is supposed to be changed after each PM action and affects the quality control chart policies. Thus, an EWMA chart is used for quality control [22].…”

“…In 3, FN(•) is the cumulative distribution function of the standard normal distribution, and K = 3/ √ n, which corresponds to the false alarm rate α = 0.0027 or an in-control ARL 1 = 370. Several studies have computed ARL 2 depending on the pre-specified optimum value of ARL 1 of 370 [22]. Srivastava and Wu [35] proposed an optimum value of λ, which minimizes ARL 2 for given ARL 1 .…”

A Model for Maintenance Planning and Process Quality Control Optimization Based on EWMA and CUSUM Control Charts

“…Therefore, this will affect the control strategy. In addition to incomplete maintenance, exponentially weighted moving average (EWMA) chart has been recently used [2].…”

Design of a Control Chart Using Extended EWMA Statistic

“…Aslam et al [7] used an EWMA statistic for exponential distribution after normal approximation, and improved the result in terms of smaller ARLs. Hariba and Tukaram [8] developed an economic design of an EWMA control chart and showed that as the shift in process mean increases, the sample size required to detect the shift decreases. Still, there is opportunity to introduce a statistic which can capitalize on the given information and is helpful in early detection of the shift.…”