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...

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...

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...

The Extended Exponentially Weighted Moving Average (extended EWMA) control chart is one of the charts and can be used to quickly detect a small shift. performance evaluated with average run length (ARL). Due deriving explicit formulas for ARL on two-sided extended EWMA trend autoregressive or AR(p) model has not been reported previously. aim this study derive as well AR(1) AR(2) models exponent...

The industrial sector is considered one of the fastest-growing sources greenhouse gases, due to excessive consumption energy required cope with growing production exhaustive products. statistical process monitoring (SPM) can be an effective tool for and controlling carbon emissions from industries. This article presents economic-statistical design combined Shewhart X¯ exponentially weighted mov...

Control charts are widely used for process monitoring. They show whether the variation is due to common causes or whether some of the variation is due to special causes. To detect large shifts in the process, Shewhart-type control charts are preferred. Cumulative sum (CUSUM) and exponentially weightedmoving average (EWMA) control charts are generally used to detect small and moderate shifts. Sh...

This paper proposes three synthetic-type control charts to monitor the mean time-between-events of a homogenous Poisson process. The first proposed chart combines an Erlang (cumulative time between events, Tr ) chart and a conforming run length (CRL) chart, denoted as Synth-Tr chart. The second proposed chart combines an exponential (or T) chart and a group conforming run length (GCRL) chart, d...

Several methods to detect faults have been developed in various fields, mainly in chemical and process engineering. However, minimal practical guidelines exist for their selection and application. This work presents an index that allows for evaluating monitoring and diagnosis performance of fault detection methods, which takes into account several characteristics, such as false alarms, false ac...

This paper investigates the detection of communication outbreaks among a small team of actors in time-varying networks. We propose monitoring plans for known and unknown teams based on generalizations of the exponentially weighted moving average (EWMA) statistic. For unknown teams, we propose an efficient neighborhood-based search to estimate a collection of candidate teams. This procedure dram...

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...