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    Economic design of VSI X̄ control chart with correlated non-normal data under multiple assignable causes

    , Article Journal of Statistical Computation and Simulation ; Volume 83, Issue 7 , Jan , 2013 , Pages 1279-1300 ; 00949655 (ISSN) Niaki, S. T. A ; Toosheghanian, M ; Gazaneh, F. M ; Sharif University of Technology
    2013
    Abstract
    It has been recently revealed that the Shewhart control charts with variable sampling interval (VSI) perform better than the traditional Shewhart chart with the fixed sampling interval in detecting shifts in the process. In most of these research works, the normality and independency of the process data or measurements are assumed and that the process is subjected to only one assignable cause. While, in practice, these assumptions usually do not hold, some recent studies are focused on working with only one or two of these violations. In this paper, the situation in which the process data are correlated and follow a non-normal distribution and that there is multiplicity of assignable causes... 

    Finding assignable cause in medium voltage network by statistical process control

    , Article IET Conference Publications ; Volume 2013, Issue 615 CP , 2013 ; 9781849197328 (ISBN) Eini, B. J ; Mirzavand, M ; Mahdloo, F ; Sharif University of Technology
    2013
    Abstract
    The current of outgoing feeders are very important data transmitted over SCADA system. Monitoring of these currents can help dispatching engineers to detect abnormality in energy consumption trend and minor faults in distribution network. Statistical process control (SPC) is one of the capable approaches which can be used for this purpose. Statistical process control is based on categorizing variations into assignable causes and random causes. In current paper we described the methods which were used for finding assignable causes in load trend and short time load variation in Alborz province power distribution company pilot project. Although this approach is not developed completely and some... 

    A probabilistic artificial neural network-based procedure for variance change point estimation

    , Article Soft Computing ; Vol. 19, issue. 3 , May , 2014 , pp. 691-700 ; ISSN: 14327643 Amiri, A ; Niaki, S. T. A ; Moghadam, A. T ; Sharif University of Technology
    Abstract
    Control charts are useful tools of monitoring quality characteristics. One of the problems of employing a control chart is that the time it alarms is not synchronic with the time when assignable cause manifests itself in the process. This makes difficult to search and find assignable causes. Knowing the real time of manifestation of assignable cause (change point) helps to find assignable cause(s) sooner and eases corrective actions to be taken. In this paper, a probabilistic neural network (PNN)-based procedure was developed to estimate the variance change point of a normally distributed quality characteristic. The PNN was selected based on trial and error among different types of... 

    A clustering approach to identify the time of a step change in shewhart control charts

    , Article Quality and Reliability Engineering International ; Volume 24, Issue 7 , 2008 , Pages 765-778 ; 07488017 (ISSN) Ghazanfari, M ; Alaeddini, A ; Akhavan Niaki, S. T ; Aryanezhad, M. B ; Sharif University of Technology
    2008
    Abstract
    Control charts are the most popular statistical process control tools used to monitor process changes. When a control chart indicates an out-of-control signal it means that the process has changed. However, control chart signals do not indicate the real time of process changes, which is essential for identifying and removing assignable causes and ultimately improving the process. Identifying the real time of the change is known as the change-point estimation problem. Most of the traditional methods of estimating the process change point are developed based on the assumption that the process follows a normal distribution with known parameters, which is seldom true. In this paper, we propose...