نتایج جستجو برای: ewma

تعداد نتایج: 564  

2015
Aamir Saghir Zhengyan Lin Ching-Wen Chen

The geometric-Poisson exponentially weighted moving average (EWMA) chart has been shown to be more effective than the Poisson EWMA chart in monitoring the number of defects in the production processes. In these applications, it is assumed that the process parameters are known or have been accurately estimated. However, in practice, the process parameters are rarely known and must be estimated f...

Journal: :International Journal of Computers Communications & Control 2010

2015
LIU Hong WANG Ping

On the basis of the AR(1) stochastic process model for consumer demand which was introduced by Professor H.L.Lee, qualified and simulation model of bullwhip effect are established when order-up-to inventory policy is employed, which investigate demand variability caused by forecasting technology, such as moving average (MA) method, exponentially weighted moving average (EWMA) method or mean squ...

Journal: :journal of optimization in industrial engineering 0
ahmad ostadsharifmemar department of industrial engineering, sharif university of technology seyed taghi akhavan niaki department of industrial engineering, sharif university of technology

in this paper, first the available single charting methods, which have been proposed to detect simultaneous shifts in a single process mean and variance, are reviewed. then, by designing proper simulation studies these methods are evaluated in terms of in-control and out-ofcontrol average run length criteria (arl). the results of these simulation experiments show that the ewma and ewms methods ...

2002
PETROS E. MARAVELAKIS JOHN PANARETOS STELIOS PSARAKIS Petros E. Maravelakis

A Measurement error is a usually met distortion factor in real-world applications that influences the outcome of a process. In this paper, we examine the effect of measurement error on the ability of the EWMA control chart to detect out-of-control situations. The model used is the one involving linear covariates. We investigate the ability of the EWMA chart in the case of a shift in mean...

Journal: :Computational Statistics & Data Analysis 2009
Petros E. Maravelakis Philippe Castagliola

The EWMA chart for the standard deviation is a useful tool for monitoring the variability of a process quality characteristic. The performance of this chart is usually evaluated under the assumption of known parameters. However, in practice, process parameters are estimated from an in-control Phase I data set. A modified EWMA control chart is proposed for monitoring the standard deviation when ...

Journal: :Technometrics 2003
Daniel W. Apley Hyun Cheol Lee

Residual-based control charts are popular methods for statistical process control of autocorrelated processes. To implement these methods, a time series model of the process is required. The model must be estimated from data, in practice, and model estimation errors can cause the actual in-control average run length to differ substantially from the desired value. This article develops a method ...

Journal: :Neurocomputing 2009
Christopher Johansson Anders Lansner

In this letter, we develop a fixed-point arithmetic, low precision, implementation of an exponentially weighted moving average (EWMA) that is used in a neural network with plastic weights. We analyze the proposed design both analytically and experimentally, and we also evaluate its performance in the application of an attractor neural network. The EWMA in the proposed design has a constant rela...

Journal: :Quality and Reliability Eng. Int. 2016
Hafiz Zafar Nazir Nasir Abbas Muhammad Riaz Ronald J. M. M. Does

Cumulative sum (CUSUM) and exponentially weighted moving average (EWMA) control charts are commonly used to detect small changes in the parameters of production processes. Recently, a new control structure was introduced, named as mixed EWMA–CUSUM control chart, which combined both charts. The current study provides a detailed comparison of these three types of control charts when the process p...

2015

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...

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