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    Change point estimation of high-yield processes experiencing monotonic disturbances

    , Article Computers and Industrial Engineering ; Vol. 67, issue. 1 , January , 2014 , p. 82-92 Niaki, S. T. A ; Khedmati, M ; Sharif University of Technology
    Abstract
    In this paper, we first propose a maximum likelihood estimator (MLE) of a change point in high-yield processes, where the only assumption is that the change belongs to a family of monotonic changes. Following a signal from the cumulative count of conforming (CCC) control chart, the performance of the proposed monotonic change-point estimator is next evaluated by comparing its performances to the ones designed for step-changes and linear-trend disturbances through extensive simulation experiments involving different single step-changes, linear-trend disturbances, and multiple-step changes. The results show that when the type of change is not known a priori, using the proposed change-point... 

    Monotonic change-point estimation of multivariate Poisson processes using a multi-attribute control chart and MLE

    , Article International Journal of Production Research ; Vol. 52, issue. 10 , Nov , 2014 , pp. 2954-2982 ; ISSN: 00207543 Niaki, S. T. A ; Khedmati, M ; Sharif University of Technology
    Abstract
    In this paper, a new multi-attribute T2 control chart is initially proposed to monitor multi-attribute processes based on a transformation technique. Then, the maximum likelihood estimator of a multivariate Poisson process change point is derived for unknown changes that are assumed to belong to a family of monotonic changes. Using extensive simulation experiments, the performance of the proposed change-point estimator is compared to the ones derived for step changes and linear-trend disturbances, when the true change types are step change, linear trends and multiple-step changes. We show when the type of the change is not known a priori, the proposed estimator is an appropriate choice,... 

    Economic design of variable sampling interval X -bar control charts for monitoring correlated non normal samples

    , Article Communications in Statistics - Theory and Methods ; Volume 42, Issue 18 , 2013 , Pages 2639-2658 ; 03610926 (ISSN) Niaki, S. T. A ; Gazaneh, F. M ; Toosheghanian, M ; Sharif University of Technology
    2013
    Abstract
    Recent studies have shown the X-bar control chart with variable sampling interval detects shifts in the process mean faster than the traditional X-bar chart. These studies are usually based on the assumption that the process data are independently and normally distributed. However, many situations in practice violate these assumptions. In this study, a methodology is developed to economically design a variable sampling interval X-bar control chart that takes into consideration correlated non normal sample data. An example is provided to illustrate the solution procedure. A sensitivity analysis on the input parameters (i.e., the cost and the process parameters) is performed taking into... 

    The Max EWMAMS control chart for joint monitoring of process mean and variance with individual observations

    , Article Quality and Reliability Engineering International ; Volume 27, Issue 4 , SEP , 2011 , Pages 499-514 ; 07488017 (ISSN) Ostadsharif Memar, A ; Niaki, S. T. A ; Sharif University of Technology
    2011
    Abstract
    A traditional approach to monitor both the location and the scale parameters of a quality characteristic is to use two separate control charts. These schemes have some difficulties in concurrent tracking and interpretation. To overcome these difficulties, some researchers have proposed schemes consisting of only one chart. However, none of these schemes is designed to work with individual observations. In this research, an exponentially weighted moving average (EWMA)-based control chart that plots only one statistic at a time is proposed to simultaneously monitor the mean and variability with individual observations. The performance of the proposed scheme is compared with one of the two... 

    Improving reliability in multistage processes with autocorrelated observations

    , Article Quality Technology and Quantitative Management ; Volume 12, Issue 2 , 2015 , Pages 143-157 ; 16843703 (ISSN) Asadzadeh, S ; Aghaie, A ; Shahriari, H ; Akhavan Niaki, S. T ; Sharif University of Technology
    Abstract
    Multistage process surveillance is considered to effectively improve the product reliability in manufacturing or service operations. To this end, the process output is commonly inspected under specific conditions and the values of the reliability-related quality characteristic are measured. However, in some cases, the observations from the process output are autocorrelated. This brings about the situation where the use of existing monitoring schemes is futile. Therefore, a class of survival analysis regression models called the proportional hazards (PH) model has been modified to justify the effect of cascade property in line with the autocorrelation issue. Subsequently, three monitoring... 

    A parameter-tuned genetic algorithm for economic-statistical design of variable sampling interval x-bar control charts for non-normal correlated samples

    , Article Communications in Statistics: Simulation and Computation ; Vol. 43, issue. 5 , 2014 , pp. 1212-1240 ; ISSN: 03610918 Akhavan Niaki, S. T ; Masoumi Gazaneh, F ; Toosheghanian, M ; Sharif University of Technology
    Abstract
    Among innovations and improvements that occurred in the past two decades on the techniques and tools used for statistical process control (SPC), adaptive control charts have shown to substantially improve the statistical and/or economical performances. Variable sampling intervals (VSI) control charts are one of the most applied types of the adaptive control charts and have shown to be faster than traditional Shewhart control charts in identifying small changes of concerned quality characteristics. While in the designing procedure of the VSI control charts the data or measurements are assumed independent normal observations, in real situations the validity of these assumptions is under... 

    A non parametric approach to monitor simple linear profiles in phases I and II

    , Article Communications in Statistics - Theory and Methods ; Volume 46, Issue 11 , 2017 , Pages 5203-5222 ; 03610926 (ISSN) Sayyad, A ; Akhavan Niaki, S. T ; Afshar Najafi, B ; Sharif University of Technology
    Taylor and Francis Inc  2017
    Abstract
    In this paper, a non parametric approach is first proposed to monitor simple linear profiles with non normal error terms in Phase I and Phase II. In this approach, two control charts based on a transformation technique and decision on beliefs are designed in order to monitor the intercept and the slope, simultaneously. Then, some simulation experiments are performed in order to evaluate the performance of the proposed control charts in Phase II under both step and drift shifts in terms of out-of-control average run length (ARL1). Besides, the performance of the proposed control charts is compared to the ones of seven other existing schemes in the literature. Simulation results show that the... 

    A grouped batch means approach to monitor autocorrelated processes

    , Article 37th International Conference on Computers and Industrial Engineering 2007, Alexandria, 20 October 2007 through 23 October 2007 ; Volume 1 , 2007 , Pages 580-588 ; 9781627486811 (ISBN) Morovatdar, R ; Akhavan Niaki, S. T ; Sharif University of Technology
    2007
    Abstract
    In order to monitor auto-correlated processes, many kinds of model-free control charts have been recently proposed based on the methods used in simulation output analysis. However, these control charts always have a restricting assumption that a large volume of observations is available while defects within them are scarce (zero-defect or high-quality processes). In this paper, we develop a new type of model-free unweighted batch means control charts, called grouped batch means (GBM) to monitor autocorrelated processes. In addition to its better performance in some cases, the GBM control chart can be applied not only to high-quality processes but also to all kinds of auto-correlated... 

    Application of the generalized linear models to represent profiles

    , Article 35th International Conference on Computers and Industrial Engineering, ICC and IE 2005, Istanbul, 19 June 2005 through 22 June 2005 ; 2005 , Pages 1-6 ; 9755612653 (ISBN); 9789755612652 (ISBN) Abbasi, B ; Akhavan Niaki, S. T ; Arkat, J ; Sharif University of Technology
    2005
    Abstract
    Statistical process control methods for monitoring processes with multivariate measurements in both the product quality variable space and process variable space are considered in this paper. Some processes, however, are better characterized by a profile or a function of quality variables. For each profile, we assume that a collection of data on the response variable along with the values of the corresponding quality variables is measured. While the linear function is the simplest, it occurs frequently that many of the nonlinear functions may be transferred to linear functions easily. This paper proposes a control chart based on the generalized linear test (GLT) to monitor coefficients of... 

    Phase-I Risk-Adjusted Geometric Control Charts to Monitor Health-care Systems

    , Article Quality and Reliability Engineering International ; 2014 ; ISSN: 1099-1638 Mohammadian, F ; Niaki, S. T. A ; Amiri, A ; Sharif University of Technology
    Abstract
    Because of the importance of health-care processes to people life, researchers attempted to reduce death rates using risk-adjusted control charts. In this paper, the number of patients survived at least 30days after a surgery is monitored using a novel risk-adjusted geometric control chart. In this chart, the patient risk is modeled using a logistic regression. The new scheme is proposed to be used in Phase-I where a likelihood ratio test derived from a change-point model is employed. The application of the proposed chart is demonstrated in a case study. Furthermore, through simulation studies, it is shown that the proposed control chart is more effective in terms of power than the chart... 

    The application of proportional hazards and frailty models to multistage processes surveillance

    , Article International Journal of Advanced Manufacturing Technology ; Volume 74, Issue 1-4 , September , 2014 , Pages 461-470 ; ISSN: 02683768 Asadzadeh, S ; Aghaie, A ; Shahriari, H ; Niaki, S. T. A ; Sharif University of Technology
    Abstract
    Monitoring industrial and service processes with the purpose of improving the product reliability has been largely addressed in the literature. The surveillance procedures have been proposed with the concentration on single-stage processes with independent quality characteristics. However, the cascade property in multistage processes entails specific monitoring methods which take into account the dependency structure among quality variables in successive stages of a process. This is referred to as regression-adjustment that justifies the heterogeneity in the study population and thus leads to optimal monitoring of multistage processes. In general, it is not straightforward to adjust a... 

    A new link function in GLM-based control charts to improve monitoring of two-stage processes with Poisson response

    , Article International Journal of Advanced Manufacturing Technology ; Vol. 72, issue. 9-12 , 2014 , p. 1243-1256 Asgari, A ; Amiri, A ; Niaki, S. T. A ; Sharif University of Technology
    Abstract
    In this paper, a new procedure is developed to monitor a two-stage process with a second stage Poisson quality characteristic. In the proposed method, log and square root link functions are first combined to introduce a new link function that establishes a relationship between the Poisson variable of the second stage and the quality characteristic of the first stage. Then, the standardized residual statistic, which is independent of the quality characteristic in the previous stage and follows approximately standardized normal distribution, is computed based on the proposed link function. Then, Shewhart and exponentially weighted moving average (EWMA) cause-selecting charts are utilized to... 

    Estimating the change point of the parameter vector of multivariate Poisson processes monitored by a multi-attribute T 2 control chart

    , Article International Journal of Advanced Manufacturing Technology ; Volume 64, Issue 9-12 , February , 2013 , Pages 1625-1642 ; 02683768 (ISSN) Niaki, S. T. A ; Khedmati, M ; Sharif University of Technology
    2013
    Abstract
    When a control chart signals an out-of-control condition, knowing when the process has really changed (the change point) accelerates the identification of the source of special causes and makes the corrective measures to be taken sooner. In this paper, a new multi-attribute T 2 control chart based on two transformation methods is initially proposed to monitor the parameter vector of multi-attribute Poisson processes. Then, the maximum likelihood estimators (MLE) of the process change point designed for both linear trend and step change disturbances are derived. Next, using Monte Carlo simulation, we show the performances of the proposed estimators are satisfactory. Finally, through... 

    A hybrid Nelder-Mead simplex and PSO approach on economic and economic-statistical designs of MEWMA control charts

    , Article International Journal of Advanced Manufacturing Technology ; Volume 65, Issue 9-12 , 2013 , Pages 1339-1348 ; 02683768 (ISSN) Barzinpour, F ; Noorossana, R ; Niaki, S. T. A ; Ershadi, M. J ; Sharif University of Technology
    2013
    Abstract
    Economic design of a control chart involves determining its basic parameters such that a cost function is minimized. This design when statistical performance measures are also considered is referred to as the economic-statistical design. In this paper, a simplex-based Nelder-Mead algorithm is used in combination with a particle swarm meta-heuristic procedure to solve both the economic and economic-statistical designs of a MEWMA control chart. The application results on extensive simulation experiments show that the particle swarm can lead the Nelder-Mead algorithm to better results. Furthermore, a comparative study is performed on the performances of three different algorithms of the... 

    Economic design of MEWMA VSSI control charts for multiattribute processes

    , Article ICORES 2012 - Proceedings of the 1st International Conference on Operations Research and Enterprise Systems ; 2012 , Pages 93-99 ; 9789898425973 (ISBN) Niaki, S. T. A ; Jahani, P ; Inst. Syst. Technol. Inf., Control Commun. (INSTICC) ; Sharif University of Technology
    2012
    Abstract
    In this research, a new methodology is developed to economically design a multivariate exponentially weighted moving average (MEWMA) control chart for multiattribute processes. The optimum design parameters of the chart, i.e., the sample size, the sampling interval, and the warning/action limit coefficients, are obtained using a genetic algorithm to minimize the expected total cost per hour. A sensitivity analysis has also been carried out to investigate the effects of the cost and model parameters on the solutions obtained  

    Multi-Objective economic statistical design of X-Bar control chart considering taguchi loss function

    , Article International Journal of Advanced Manufacturing Technology ; Volume 59, Issue 9-12 , April , 2012 , Pages 1091-1101 ; 02683768 (ISSN) Safaei, A. S ; Kazemzadeh, R. B ; Niaki, S. T. A ; Sharif University of Technology
    2012
    Abstract
    Shewhart charts are the most popular control charts that can be used to monitor variable quality characteristics in a production process. In this paper, a multi-objective model of the economic statistical design of the X-bar control chart is first proposed by incorporating the Taguchi loss function and the intangible external costs. The model minimizes the mean hourly loss cost while minimizing out-of-control average run length and maintaining reasonable in-control average run length. A multiobjective evolutionary algorithm, namely NSGA-II, is then developed and used to obtain the Pareto optimal solution of the model. Some sensitivity analyses are next performed to investigate the effect of... 

    A hybrid ant colony, Markov chain, and experimental design approach for statistically constrained economic design of MEWMA control charts

    , Article Expert Systems with Applications ; Volume 39, Issue 3 , February , 2012 , Pages 3265-3275 ; 09574174 (ISSN) Niaki, S. T. A ; Ershadi, M. J ; Sharif University of Technology
    2012
    Abstract
    The multivariate exponentially weighted moving average, MEWMA, control chart is an effective statistical tool for detecting small shifts in process mean vectors. On the one hand, the economic design process of a MEWMA control chart involves determining the main parameters of the chart, namely, the sample size n, the sampling interval h, the smoothing constant r, and the control limit L such that a quality cost function is minimized. On the other hand, the statistically constrained economic design of MEWMA chart is to determine the chart parameters such that a cost function is minimized while the statistical performance of the chart is maintained at a desire level. In this paper, the... 

    A particle swarm optimization approach on economic and economic-statistical designs of MEWMA control charts

    , Article Scientia Iranica ; Volume 18, Issue 6 , December , 2011 , Pages 1529-1536 ; 10263098 (ISSN) Niaki, S. T. A ; Malaki, M ; Ershadi, M. J ; Sharif University of Technology
    2011
    Abstract
    Control charts are the best tools to monitor main process parameters, and the Multivariate Exponentially Weighted Moving Average, MEWMA, type of this tool is used when there are several correlated quality characteristics to be monitored simultaneously where detecting small deviations of the characteristics is desired. In this paper, the models of both the economic and the economic-statistical design problems of MEWMA control charts are solved by a Particle Swarm Optimization (PSO) approach. The comparison study between the economic and the economic-statistical designs shows better statistical performances of the economic-statistical design with negligible increase in cost. Furthermore, in... 

    Change-point estimation of the process fraction non-conforming with a linear trend in statistical process control

    , Article International Journal of Computer Integrated Manufacturing ; Volume 24, Issue 10 , 2011 , Pages 939-947 ; 0951192X (ISSN) Zandi, F ; Niaki, S. T. A ; Nayeri, M. A ; Fathi, M ; Sharif University of Technology
    Abstract
    Despite the fact that control charts are able to trigger a signal when a process has changed, it does not indicate when the process change has begun. The time difference between the changing point and a signal of a control chart could cause confusions on the sources of the problems. Knowing the exact time of a process change would help to reduce the time for identification of the special cause. In this article, a model for the change-point problem is first introduced and a maximum-likelihood estimator (MLE) is applied when a linear trend disturbance is present. Then, Monte Carlo simulation is applied in order to evaluate the accuracy and the precision performances of the proposed... 

    Drift change point estimation in multistage processes using MLE

    , Article International Journal of Reliability, Quality and Safety Engineering ; Volume 22, Issue 5 , October , 2015 ; 02185393 (ISSN) Safaeipour, A ; Akhavan Niaki, S. T ; Sharif University of Technology
    World Scientific Publishing Co. Pte Ltd  2015
    Abstract
    Usually the time a control chart shows an out-of-control signal is not the exact time at which a change happens; instead, the change has started before this time. The exact time the change starts is called the change point. Although many manufacturing processes are of a multistage type, most of change point estimations in the literature focused on processes with a single stage. In this research, a multistage process with a single quality characteristic monitored in each stage is first modeled using both a first-order autoregressive (AR(1)) and an autoregressive moving average (ARMA(1, 1)) model. Then, a maximum likelihood estimator is derived to estimate the change points, i.e., the sample...