Shewhart control charts have previously been suggested as a process control tool for use in routine linear accelerator (linac) output verifications. However, a comprehensive approach to process control has not been investigated for linac output verifications. The purpose of this work is to investigate a comprehensive process control approach to linac output constancy quality assurance (QA). The...

Nonparametric control charts can provide a robust alternative in practice to the data analyst when there is a lack of knowledge about the underlying distribution. A nonparametric exponentially weighted moving average (NPEWMA) control chart combines the advantages of a nonparametric control chart with the better shift detection properties of a traditional EWMA chart. A NPEWMA chart for the media...

The performance of an X-bar chart is usually studied under the assumption that the process standard deviation is well estimated and does not change. This is, of course, not always the case in practice and X-bar charts are not robust against errors in estimating the process standard deviation or changing standard deviation. In this paper, the use of an exponentially weighted moving average (EWMA...

Quality control is an important role in industry for maintain quality stability. Statistical process can quickly investigate the occurrence of unforeseen causes or shifts using charts. Mixed Exponentially Weighted Moving Average - Cumulative Sum (MEC) chart a tool used to monitor and evaluate whether production not. The MEC method combination (EWMA) (CUSUM) Combining two charts aims increase se...

BACKGROUND Influenza viruses cause seasonal outbreaks in temperate climates, usually during winter and early spring, and are endemic in tropical climates. The severity and length of influenza outbreaks vary from year to year. Quick and reliable detection of the start of an outbreak is needed to promote public health measures. METHODS We propose the use of an exponentially weighted moving aver...

Joint monitoring of time and magnitude is an important issue in many industrial non-industrial fields several proposals exist the literature. The aim this article to propose a new maximum exponentially weighted moving average (Max-EWMA) chart assuming generalized exponential distribution for as well magnitude. As test-statistic Max-EWMA consists two EWMA statistics, it easy identify out-of-cont...

Identifying convergence in numerical optimization is an ever-present, difficult, and often subjective task. The statistical framework of Gaussian process surrogate model optimization provides useful measures for tracking optimization progress; however, the identification of convergence via these criteria has often provided only limited success and often requires a more subjective analysis. Here...

Most SPC approaches for detecting the process variance assume that it remains constant over time. However, these approaches may not be well handled with the case in which patterned changes exist. In this paper, we propose a new control chart which integrates EWMA procedure with generalized likelihood ratio (GLR) test statistics for monitoring patterned variance shifts. It can be easily designed...

a manufacturing process cannot be released to production until it has been proven to be stable. also, we cannot begin to talk about process capability until we have demonstrated stability in our process. this means that the process variation is the result of random causes only and all assignable or special causes have been removed. in complicated manufacturing processes, such as drilling proces...

Control charts are used to detect assignable causes in different manufacturing and nonmanufacturing processes. This study presents a new maximum exponentially weighted moving average (Max-EWMA) chart for joint unit interval time magnitude monitoring. To this end, beta distribution is considered whereas simplex magnitude. Average run length (ARL), standard deviation of (SDRL), quantiles evaluate...