Sharif Digital Repository

This effort attempts to study the change point problem in the area of non-linear profiles. Two methods for estimating the time of a single step change is proposed. In the first method a model consisting of two networks which is based on artificial neural networks is proposed. These networks are different only in their training data. One network is trained for ascending segments of the profile and the other is trained for descending segments of the profile. In the second method the maximum likelihood estimator (MLE) of the single step change is analyzed. Due to the complexity of estimating the parameters of the non-linear model by MLE, this estimator is based on the difference between the... 

This effort attempts to study the multiple change-point problem in the area of non-linear profiles. Two methods for estimating the times of multiple change-points is proposed. In the first method, a model consisting of two networks, which is based on artificial neural networks, is proposed. These networks are distinctive only in their training data. One network is trained for ascending segment of the profile and the other is trained for descending segments of the profile. In the second method, Bayesian approach is proposed for estimating multiple change-point. While using Bayesian approach the parameters of the Non-linear model must be estimated. However, this issue is complicated or... 

Profile Monitoring is a new research topics in the field of statistical process control. In many applications of statistical quality control, sometimes quality of a process or product described by a relationship between a response variable and one or more independent variables.The researchers call this relationship profile. The study seeks to demonstrate that monitoring profiles In addition, the industry can be effective in medical field and improves control of the patient's condition by a doctor. Profiles are usually modeled with a linear regression equation, non-linear or polynomial. finally, the results of this study, using actual data, models and methods to predict and control... 

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... 

Nowadays, due to the advancement in manufacturing technology and increasing use of information technology in the services and industries, most of production proccess consist of complex and high-dimensional data. These processes include multivariate processes, complex profiles and multistage processes. In some quality control applications, processes consist of multiple components, stations or stages to finish the final product or service which are called multistage processes. In addition, some quality characteristics in each stage can be represented by a relationship between a response variable and one or more explanatory variables which is named as profile. In this research, a general model... 

Lipopolysaccharide (LPS), also known as endotoxin, is a highly toxic component exists in the outer membrane of gram negative bacteria. It releases into the environment during every phase of bacterial growth cycle, so it causes contamination of a wide range of biopharmaceutical products. Even small quantities of endotoxin injected to human body can result in fever, septic shock, and death. Therefore, it is highly important to detect and also quantify endotoxin of biopharmaceutical products in quality control laboratories. The most validated method used for endotoxin detection is Limulus Amebocyte Lysate (LAL). Although this method is sensitive, it has some unavoidable drawbacks such as highly... 

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... 

Hospitals increasingly use control charts to monitor clinical processes and their outcomes. In medical context, control charts should have stable performance when different patients with different levels of risk enter the hospital. In order to monitor multi-attribute medical processes, we propose a new control chart with entities having different levels of risk. First, risk-adjusted multivariate cumulative sum control chart (RA-MCUSUM) is developed. Then, simulation experiences are performed to demonstrate the application and to evaluate RA-MCUSUM performance in terms of in-control average run length (ARL0) stability with the one of a standard MCUSUM chart.The results show that while the... 

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... 

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... 

There are a variety of multivariate industrial processes in real world problems. It seems to be necessary to control them through strong tools such as control charts. One of the state-of-the-art methods to monitor processes is neural network. Neural networks are data processing systems inspired by human brain and they are capable of processing data with a variety of small processors working in parallel forming an integrated network to solve a problem. Chaotic models, one of the states of being out of control, are deterministic non-linear models which have extremely complex behavior under determined assumption. Researches have shown neural networks have excellent performance in such systems.... 

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... 

Statistical process control charts have been applied to the health care practices for quite same time. This work aims at investigating the merits to of applying process control chart to the survival time of the patients suffering from gastric cancer-who go though the surgical treatment. Based on accelerated failure time regression models we adopt risk adjusted control chart to monitor the surgical outcome. The monitoring process will we performed continuously based on a likelihood ratio test. The result indicate that this risk adjusted model can provide better estimation for the risk adjustment model parameters. As expected, the proposed risk-adjusted control charts can achieve a better... 

Recently, a new method to investigate chip seal performance has developed by a research team at Sharif University of Technology. This study investigates the effect of various additives such as CRM, SBR Latex, Hydrated Lime and Ordinary Portland Cement (OPC), on the curing time of chip seal by this method. In addition, the chip seal treatments were investigated in different climate conditions like Wet and Wet-Freeze zones. The overall performance of mixture specimens evaluated using creep loading test. In fact, the bonding properties between aggregates and surface of Hot Mix Asphalt measured. The test results were analyzed by using of the work and time parameters. These parameters were... 

Control charts are the most important tools of statistical quality control. The problem that exists is that control charts do not show the real time the shift in a process started. The real time a change occurs in a process is called the change point. In this research, the monotonic change point in a multivariate normal process is estimated using the maximum likelihood estimation approach, where the process is monitored by a multivariate exponentially weighted moving average scheme. Mote Carlo simulation studies are performed to evaluate the performance of the proposed approach  

Quality Assurance is one of the crucial steps in software production and should be repeated. These days, software companies are using continuous integration (CI) pipelines for building software and controlling software quality. Regression test, is a test which is performed after each change in software, to assess the quality of the software system and its ability to meet functional and non-functional needs. Each execution of this test, leads to infrastructure costs and a waste of time for the software development team. The reason is that the development team has to wait until the test is completed to ensure that the changes are correct. To reduce this cost, methods such as prioritizing and... 

Chip seal is one of the most economical pavement maintenance practice that extends pavement life. To ensure chip seal good performance several quality control methods have been developed. However, most of these methods are qualitative and only measure the stone loss under a certain number on loading. This research developed a new method for quality control of chip seal, based on the assumption that characteristics of the bond between chips and pavement surface play a key role in chip seal performance. To validate this test method, the authors used a wheel track loading test. The results from this research clearly showed that the characteristics of the bond between chips and pavement surface...