Showing 28 results for Control
A. Arefmanesh, M. Najafi, H. Abdi ,
Volume 18, Issue 4 (12-2007)
Abstract
Abstract : The meshless local Petrov-Galerkin method with unity as the weighting function has been applied to the solution of the Navier-Stokes and energy equations. The Navier-Stokes equations in terms of the stream function and vorticity formulation together with the energy equation are solved for a driven cavity flow for moderate Reynolds numbers using different point distributions. The L2-norm of the error as a function of the size of the control volumes is presented for different cases and the rate of convergence of the method is established. The results of this study show that the proposed method is applicable in solving a variety of non-isothermal fluid flow problems.
M. Ghazanfari, K. Noghondarian, A. Alaedini,
Volume 19, Issue 4 (12-2008)
Abstract
Although control charts are very common to monitoring process changes, they usually do not indicate the real time of the changes. Identifying the real time of the process changes is known as change-point estimation problem. There are a number of change point models in the literature however most of the existing approaches are dedicated to normal processes. In this paper we propose a novel approach based on clustering techniques to estimate Shewhart control chart change-point when a sustained shift is occurrs in the process mean. For this purpose we devise a new clustering mechanism, a new similarity measure and a new objective function. The proposed approach is not only capable of detecting process change-points, but also automatically estimates the true values of the out-of-control parameters of the process. We also compare the performance of the proposed approach with existing methods.
M. Rafeeyan ,
Volume 19, Issue 7 (8-2008)
Abstract
In this paper a non-diagonal regulator, based on the QFT method, is synthesized for an uncertain MIMO plant whose output and control signals are subjected to hard time-domain constraints. This procedure includes the design of a non-diagonal pre-controller based on a new simple approach, followed by the sequential design of a diagonal QFT controller. We present a new formulation for the latter stage, which shows the role of off-diagonal elements in the design procedure. A numerical example is given to illustrate the effectiveness of the proposed method .
Hamed. R. Tareghian , Madjid Salari,
Volume 20, Issue 3 (9-2009)
Abstract
The dynamic nature of projects and the fact that they are carried out in changing environments, justify the need for their periodic monitoring and control. Collection of information about the performance of projects at control points costs money. The corrective actions that may need to be taken to bring the project in line with the plan also costs money. On the other hand, penalties are usually imposed when due to “no monitoring” policies projects are delivered later than expected. Thence, this paper addresses two fundamental questions in this regard. First question concerns the optimal frequency of control during the life cycle of a project. The second question concerns the optimal timing of control points. Our solution methodology consists of a simulation-optimization model that optimizes the timing of control points using the attraction-repulsion mechanisms borrowed from the electromagnetism theory. A mathematical model is also used to optimally expedite the remaining part of the project when possible delays are to be compensated.
Rassoul Noorossana, Abbas Saghaei , Mehdi Dorri,
Volume 21, Issue 4 (12-2010)
Abstract
In an increasing number of practical situations, the quality of a process or product can be effectively characterized and summarized by a profile. A profile is usually a functional relationship between a response variable and one or more explanatory variables which can be modeled frequently using linear or nonlinear regression models. In this paper, we study the effect of non-normality on profile monitoring in Phase II when within or between autocorrelation is present. Different levels of autocorrelation and skewed and heavy-tailed symmetric non-normal distributions are used in our study to evaluate the performance of three existing monitoring schemes numerically. Simulation results indicate that the non-normality and autocorrelation can have a significant effect on the in-control performances of the considered schemes. Results also indicate that the out-of-control performances of the schemes are not very sensitive to low and moderate levels of autocorrelation in moderate and large shifts .
Meysam Zareiee, Abbas Dideban, Ali A. Orouji ,
Volume 22, Issue 2 (6-2011)
Abstract
Discrete event system, Supervisory control, Petri Net, Constraint |
This paper presents a method to manage the time in a manufacturing system for obtaining an optimized model. The system in this paper is modeled by the timed Petri net and the optimization is performed based on the structural properties of Petri nets. In a system there are some states which are called forbidden states and the system must be avoided from entering them. In Petri nets, this avoidance can be performed by using control places. But in a timed Petri net, using control places may lead to decreasing the speed of systems. This problem will be shown on a manufacturing system. So, a method will be proposed for increasing the speed of the system without using control places .
Mohammad Saber Fallahnezhad, Hasan Hosseini Nasab,
Volume 22, Issue 3 (9-2011)
Abstract
M. Miranbeigi, A.a. Jalali, A. Miranbeigi ,
Volume 22, Issue 3 (9-2011)
Abstract
supply chain network receding horizon control demand move suppression term |
Supply chain networks are interconnection and dynamics of a demand network. Example subsystems, referred to as stages, include raw materials, distributors of the raw materials, manufacturers, distributors of the manufactured products, retailers, and customers. The main objectives of the control strategy for the supply chain network can be summarized as follows: (i) maximize customer satisfaction, and (ii) minimize supply chain operating costs. In this paper, we applied receding horizon control (RHC) method to a set of large scale supply chains of realistic size under demand disturbances adaptively. Also in order to increase the robustness of the system , we added a move suppression term to cost function .
S Moslehpour, K Jenab, N. Namburi,
Volume 22, Issue 4 (12-2011)
Abstract
Radio Frequency Identification (RFID) is used to identify the characteristics of an object wirelessly using radio waves. The purpose of this technology in this study is mainly focused on healthcare for inventory management and theft control replacing the manual logs. The storage and tracking of high-cost inventory items is developed. Automatic reordering and billing interfaces are designed for the inventory falling below the par levels. iRISupply and iRIScope are the two RFID systems developed to reduce the inventory costs, expired item costs and to improve the inventory management with easy reporting system .
Mehdi Kabiri Naeini, Mohammad Saleh Owlia, Mohammad Saber Fallahnezhad,
Volume 23, Issue 3 (9-2012)
Abstract
In this research, an iterative approach is employed to recognize and classify control chart patterns. To do this, by taking new observations on the quality characteristic under consideration, the Maximum Likelihood Estimator of pattern parameters is first obtained and then the probability of each pattern is determined. Then using Bayes’ rule, probabilities are updated recursively. Finally, when one of the updated derived statistics falls outside the calculated control interval a pattern recognition signal is issued. The advantage of this approach comparing with other existing CCP recognition methods is that it has no need for training. Simulation results show the effectiveness and accuracy of the new method to detect the abnormal patterns as well as satisfactory results in the estimation of pattern parameters.
Abbas Saghaei, Maryam Rezazadeh-Saghaei, Rasoul Noorossana, Mehdi Doori,
Volume 23, Issue 4 (11-2012)
Abstract
In many industrial and non-industrial applications the quality of a process or product is characterized by a relationship between a response variable and one or more explanatory variables. This relationship is referred to as profile. In the past decade, profile monitoring has been extensively studied under the normal response variable, but it has paid a little attention to the profile with the non-normal response variable. In this paper, the focus is especially on the binary response followed by the bernoulli distribution due to its application in many fields of science and engineering. Some methods have been suggested to monitor such profiles in phase I, the modeling phase however, no method has been proposed for monitoring them in phase II, the detecting phase. In this paper, two methods are proposed for phase II logistic profile monitoring. The first method is a combination of two exponentially weighted moving average (EWMA) control charts for mean and variance monitoring of the residuals defined in logistic regression models and the second method is a multivariate T2 chart to monitor model parameters. The simulation study is done to investigate the performance of the methods.
Abbas Dideban, Maysam Zareiee, Ali A. Orouji, Hassan Rezaei Soleymanpour ,
Volume 24, Issue 1 (2-2013)
Abstract
This paper deals with the problem of forbidden states in discrete event systems modeled by Petri Net. To avoid the forbidden states, some constraints which are called Generalized Mutual Exclusion Constraints can be assigned to them. Enforcing these constraints on the system can be performed using control places. However, when the number of these constraints is large, a large number of control places must be connected to the system which complicates the model of controller. In this paper, the objective is to propose a general method for reducing the number of the mentioned constraints and consequently the number of control places. This method is based on mixing some constraints for obtaining a constraint verifying all of them which is performed using the optimization algorithms. The obtained controller after reducing the number of the control places is maximally permissive.
Alireza Sharafi, Majid Aminnayeri, Amirhossein Amiri, Mohsen Rasouli,
Volume 24, Issue 2 (6-2013)
Abstract
Identification of a real time of a change in a process, when an out-of-control signal is present is significant. This may reduce costs of defective products as well as the time of exploring and fixing the cause of defects. Another popular topic in the Statistical Process Control (SPC) is profile monitoring, where knowing the distribution of one or more quality characteristics may not be appropriate for discussing the quality of processes or products. One, rather, uses a relationship between a response variable and one or more explanatory variable for this purpose. In this paper, the concept of Maximum Likelihood Estimator (MLE) applied to estimate of the change point in binary profiles, when the type of change is drift. Simulation studies are provided to evaluate the effectiveness of the change point estimator.
Shervin Asadzadeh , Abdollah Aghaie, Hamid Shahriari ,
Volume 24, Issue 2 (6-2013)
Abstract
Monitoring the reliability of products in both the manufacturing and service processes is of main concern in today’s competitive market. To this end, statistical process control has been widely used to control the reliability-related quality variables. The so-far surveillance schemes have addressed processes with independent quality characteristics. In multistage processes, however, the cascade property must be effectively justified which entails establishing the relationship among quality variables with the purpose of optimal process monitoring. In some cases, measuring the values corresponding to specific covariates is not possible without great financial costs. Subsequently, the unmeasured covariates impose unobserved heterogeneity which decreases the detection power of a control scheme. The complicated picture arises when the presence of a censoring mechanism leads to inaccurate recording of the process response values. Hence, frailty and Cox proportional hazards models are employed and two regression-adjusted monitoring procedures are constructed to effectively account for both the observed and unobserved influential covariates in line with a censoring issue. The simulation-based study reveals that the proposed scheme based on the cumulative sum control chart outperforms its competing procedure with smaller out-of-control average run length values.
Mohammad Saber Fallah Nezhad,
Volume 24, Issue 4 (12-2013)
Abstract
In this research, the decision on belief (DOB) approach was employed to analyze and classify the states of uni-variate quality control systems. The concept of DOB and its application in decision making problems were introduced, and then a methodology for modeling a statistical quality control problem by DOB approach was discussed. For this iterative approach, the belief for a system being out-of-control was updated by taking new observations on a given quality characteristic. This can be performed by using Bayesian rule and prior beliefs. If the beliefs are more than a specific threshold, then the system will be classified as an out-of-control condition. Finally, a numerical example and simulation study were provided for evaluating the performance of the proposed method.
Seyed Mojtaba Jafari Henjani, Valeriy Severin,
Volume 25, Issue 3 (7-2014)
Abstract
The paper is devoted to solution of some problems in nuclear power station generating unit intellectual control systems using genetic algorithms on the basis of control system model development, optimizations methods of their direct quality indices and improved integral quadratic estimates. Some mathematical vector models were obtained for control system multicriterion quality indices with due consideration of stability and quality indices criteria, this increasing the reliability of optimal control system synthesis. Optimal control systems with fuzzy controllers were synthesized for nuclear reactor, steam generator and steam turbine, thus allowing comparison between fuzzy controllers and traditional PID controllers. Mathematical models built for nuclear power station generating unit control systems, including nuclear reactor, steam generator, steam turbine and their control systems interacting under normal operational modes, which permitted to perform parametrical synthesis of system and to study various power unit control laws. On the basis of power unit control system models controllers were synthesized for normal operational modes.
Romina Madani, Amin Ramezani, Mohammad Taghi Madani Beheshti,
Volume 25, Issue 4 (10-2014)
Abstract
Today, companies need to make use of appropriate patterns such as supply chain management system to gain and preserve a position in competitive world-wide market. Supply chain is a large scaled network consists of suppliers, manufacturers, warehouses, retailers and final customers which are in coordination with each other in order to transform products from raw materials into finished goods with optimal placement of inventory within the supply chain and minimizing operating costs in the face of demand fluctuations. Logistics is the management of the flow of goods between the point of origin and the point of consumption. One issue in Logistics management is the presence of possible long delays in goods transportation. In order to handle long delays, there are two possible solutions proposed in this paper. One solution is to use Model Predictive Controllers (MPCs) using orthonormal functions (Laguerre functions) and the other is to change supply chain model in which an integrator is imbedded. To this end, the two mentioned solutions will be implemented on a supply chain with long logistics delays and the results will be compared to classical MPC without using orthonormal basis and augmented model for different type of customer demand (constant, pulse and random demand).
Mohammad Saber Fallah Nezhad, Vida Golbafian, Hasan Rasay, Yusef Shamstabar,
Volume 28, Issue 3 (9-2017)
Abstract
CCC-r control chart is a monitoring technique for high yield processes. It is based on the analysis of the number of inspected items until observing a specific number of defective items. One of the assumptions in implementing CCC-r chart that has a significant effect on the design of the control chart is that the inspection is perfect. However, in reality, due to the multiple reasons, the inspection is exposed to errors. In this paper, we study the economic-statistical design of CCC-r charts when the inspection is imperfect. Minimization of the average cost per produced item is considered as the objective function. The economic objective function, modified consumer risk, and modified producer risk are simultaneously considered, and then the optimal value of r parameter is selected.
Rassoul Noorossana, Mahnam Najafi,
Volume 28, Issue 4 (11-2017)
Abstract
Change point estimation is as an effective method for identifying the time of a change in production and service processes. In most of the statistical quality control literature, it is usually assumed that the quality characteristic of interest is independently and identically distributed over time. It is obvious that this assumption could be easily violated in practice. In this paper, we use maximum likelihood estimation method to estimate when a step change has occurred in a high yield process by allowing a serial correlation between observations. Monte Carlo simulation is used as a vehicle to evaluate performance of the proposed method. Results indicate satisfactory performance for the proposed method.
Babak Shirazi,
Volume 28, Issue 4 (11-2017)
Abstract
Resource planning in large-scale construction projects has been a complicated management issue requiring mechanisms to facilitate decision making for managers. In the present study, a computer-aided simulation model is developed based on concurrent control of resources and revenue/expenditure. The proposed method responds to the demand of resource management and scheduling in shell material embankment activities regarding large-scale dam projects of Iran. The model develops a methodology for concurrent management of resources and revenue/expenditure estimation of dam's projects. This real-time control allows managers to simulate several scenarios and adopt the capability of complicated working policies. Results validation shows that the proposed model will assist project managers as a decision support tool in cost-efficient executive policymaking on resource configuration.
