Sharif Digital Repository

Knowing the time of change would narrow the search to find and identify the variables disturbing a process. Having this information, an appropriate corrective action could be implemented and valuable time could be saved. Multistage processes that are often observed in current manufacturing processes must be monitored to assure quality products. The change-point detection of such processes has not been proposes investigated yet. Thus, this dissertation proposes maximum likelihood step-change estimators of two kinds of these processes. First, a multistage process with variable quality characteristics is considered and formulated by the first-order auto-regressive model. For the location... 

In this research, we consider the application of copulas in multivariate quality control problems. In particular, we consider two specific problems. The first problem concerns the situation where the normality assumption is rejected. In this case, copulas can be used as a flexible tool to define a broad range of multivariate distributions with different dependence structure as well as marginal distributions. The second problem concerns proposing control charts to monitor the dependence structure among quality characteristics. The proposed method not only produces an out-of-control signal when dependence structure among variables deviates from the specified one, but also can be used to... 

Water demand forecasting and modeling is very important and needful in water resource planning and management as well as water consumption forecasting. The forecasting helps the managers to design and operate various infrastructures of water supply such as tanks and other distribution equipments. Nowadays, intelligent systems are very efficient and practical tools because of their high ability in forecasting and independency from limitative assumptions in classic methods. In this thesis, one of the newest methods, called support vector regression method, is used to forecast monthly demands of water consumption in Tehran, Iran. To develop the method, data is first preprocessed through... 

In a production process, when the quality of a product depends on more than one characteristic, and there is correlation between them, using univariate control charts increases type І and type ΙΙ errors. So for monitoring these processes, multivariate quality control charts are used. Multivariate statistical process control is receiving increased attention in the literature,but little work has been done to deal with multi-attribute processes and just in recent years some techniques are developed in this field. In this thesis, based on the power transformation concept, two new techniques have been developed to monitor multi-attribute processes, in which the defect counts are important. In the... 

Control charts are one of the most important tools in statistical process control to detect assignable causes. The goal of a control chart is to detect an out-of-control state quickly so that process engineers can initiate their search for the special cause sooner. Once the special cause has been identified, the appropriate action can then be taken to improve the process.A new method to estimate the change point of Poisson rate parameter when the step change occurs is proposed in this thesis. That is, the rate parameter is assumed to suddenly shift from its in-control value to an out-of control value at a single unknown point in the process.To do this, a belief that the process is in-control... 

In this research, a new Bayesian method for constructing confidence intervals on the parameters of any continuous distribution is first developed. The main idea behind developing this method is to model uncertainty. As an application of the proposed methodology, confidence intervals for the two parameters of the Weibull distribution along with their joint confidence interval are then derived in which data can be of type I censored data, type II censored data or uncensored. The new confidence intervals are next compared to other existing exact confidence intervals in the literature and shown to have better performances. Furthermore, we show the lengths of the existing exact confidence... 

Nowadays, simulation science supports a wide range of researches. This science is in a constant improvement process. Simulation is a process to fulfill the real world problems by means of experiments which resemble to the real world situation so much. One of the preconditions in statistical simulation is to produce the random number and variables based on the presumed attributes and parameters. In this research, at first, a simple and fast responding algorithm to generate correlated uniformly distributed tri-dimensional vectors is proposed. In this algorithm by producing three groups of random numbers, we can produce tri-dimensional vectors of correlated uniformly distributed based on... 

Control charts are one of the most important statistical process control tools used in monitoring processes and improving the quality by decreasing the variability of processes. In spite of various applications for multi-attribute control charts in industries and service sectors, only a few research efforts have been performed in developing this type of control charts. The developed multivariate control charts are all based on the assumption that the quality characteristics follow a multivariate Normal distribution while, in many applications the correlated quality characteristics that have to be monitored simultaneously are of attribute type and follow distributions such as multivariate... 

In this work, effects of information aggregation on risk attitude of Iranian individuals is being studied through two experiments. In these experiments a risk-free asset with a guaranteed revenue and a risky asset is introduced to each individual. Then the individual has to allocate a certain amount of money between two assets. In both experiments three treatments of control, separation and aggregation are defined in a way that the degree of information aggregation increases respectively. Given the specific treatment assigned to each individual, complementary information is presented, in orderto finalize the decision. Next a financial market simulation for a five year horizon is conducted to... 

Since little attention has been given to multiattribute compared to multivariate control charts, this research is concerned with developing a new methodology to employ the multivariate exponentially weighted moving average (MEWMA) charts for multi-attribute processes. Moreover, since the variable sample size and sampling interval (VSSI) MEWMA charts detect small process mean-shifts faster than the traditional MEWMA, an economic design of VSSI MEWMA chart is proposed to obtain the optimum design parameters of the chart. The sample size, the sampling interval, and the warning/action limit coefficients are obtained using a genetic algorithm such that the expected total cost per hour is... 

Nowadays,The use of employ of Simulation techniques to estimate different determine characteristics and analyze of any kinds of various systems performance measures has increaseds drastically. The output analysis in simulation plays a key role to obtain the estimates. Consequently, in a given simulation project, whether it is terminating or steady state, the use of statistical approaches to analyze output data derived by running the simulation model is inevitable.During a given Simulation project, most of time is devoted to build, and run a model; however, to analyze the outputs of model plays a key role to obtain desire goals of project. Consequently, in a predefine simulation project,... 

Monitoring a surgical process has gained prominence by accounting for patiens̛ health condition prior to surgery in recent years. How even most existing researches focus on phase 2 monitoring and binary outcomes. Very little work has been done on phase 1 control of outcomes and no one addressing the issue of phase 1 monitoring of continuous outcomes. Risk adjustment is accomplished using accelerated failure time (AFT) regression models. In this thesis a general phase 1 risk-adjusted control chart is proposed for monitoring continuous surgical outcomes based on a likelihood-ratio test derived from a change-point model. Different from the existing models, this thesis shows that continuous... 

Control chart is one of the most powerful tools in statistical process control (SPC). This tool has been widely used in industrial schemes; however, in recent years, it has become widespread in health care studies as well. Most of these studies are dealing with monitoring qualitative variables in one-stage processes. This research presents a new mechanism for monitoring medical processes, by modelling the bone marrow transplant surgery as a dependent multi-stage process into a multiple profile. In this mechanism, the characteristics which will be monitored are quantitative, and the cascade property between stages is considered. Moreover, risk adjustment methods have been used due to the... 

In modern industries, multivariate multistage auto-correlated processes are widely used to ensure productivity and product quality. Interconnections between work stations bring a challenging task in detecting various shifts and identifying their root causes. In addition, simultaneous monitoring process mean and variability with single control chart methods has gained considerable attention throughout these years. In this article, a double-max multivariate exponentially weighted moving average (DM-MEWMA) chart is proposed based on two novel statistics to monitor the parameters of multivariate multistage auto-correlated processes jointly. Prior knowledge of variation propagation has been used... 

Control charts are considered as one of the most important tools of statistical process control in detection of assignable causes of variation in the processes. One of the main criticisms of these charts is their inability in discovering the out-of-control state in real time. To eliminate the main sources of error, indicating the actual time of deviation in processes which is called change point is very important. Diagnosing of real time of changes limits the range of search for the causes of deviations and maximizes the chance of finding the main sources of deviation resulting in time saving and reducing expenses. There are different types of change points. One of change point types which... 

In this project, we intend to use intelligent and learning algorithms to forecast the U.S. presidential elections. First, we considered some economic and political variables in our model. Then by using stepwise regression, we found the most significant variables. After that, we used three data mining techniques on these data. In the next step, we used support vector regression and neural networks to predict the elections. Then we compared these two algorithms with each other. Eventually, we realized how strong and accurate these methods are to predict the U.S. presidential elections. We have, also, proved that using data mining techniques is beneficial to make models more accurate  

Nowadays due to the advancement in technology, most of the production processes consist of several dependent stages and the quality characteristics of products at each stage depends not only on the operation at the current stage but also to the quality characteristics at the upstream stages. In other words, the disturbance in the quality characteristics of each stage would propagate to the downstream stages and affects the quality of the products at downstream stages. This property is referred to as the cascade property of multistage processes. However, the most of the conventional SPC tools were developed based on the assumption of processes with single stage or processes with multiple... 

Supply chain has gained great interest from researchers in recent years. In this regard, proposing efficient and practical models that reflect different supply chain aspects is challenging. This research deals with an integrated production-distribution supply chain model which incorporates few parties along with some processes to obtain raw materials from raw material suppliers and to convert them to semi and final products and then distribute them indirectly using warehouses to end users. To tackle the problem, we propose a mixed integer linear programming model. Due to the combinatorial nature of the problem, a metaheuristic algorithm is designed to solve industrial size problems.... 

These days, most companies are creating Closed-loop Supply Chains or they are adding Reverse Supply Chain to their existing Forward Supply Chain. Reducing raw material consumption, profit, customer satisfaction and environmental laws are most important reasons of this phenomenon. In the Closed-loop Supply Chains, companies collect the end of life and the end of use products and then if the quality of the returned product is good enough, that product with be refurbished and will be sold again and if the quality of returned products is not good enough to be refurbished, companies will use its good parts in manufacturing new products and the rest of the parts would be sent to disposal centers.... 

The main purpose of this research is to consider the operational machine cost in the shop floor scheduling, which is not considered in the literature thoroughly. To this end, four types of problems in the parallel machine environment are studied with the objectives of minimizing makespan and total cost. Accordingly, the problems are as type of multi-objective optimization, so we choose the approach of finding Pareto optimal solutions to solve them. In these problems we have considered unrelated parallel machines, uniform parallel machines, and the cases of existence or non-existence of sequence dependent setup times and costs. In order to solve the problems, various approaches, with respect...