Sharif Digital Repository

This is the first attempt at process modeling in terms of predictive control using a hierachical method based on regression analysis and artificial neural networks(ANNs).This hierachical use leads to the reliability improvement of neural model of process in prediction (extrapolation and interpolation) of process output. such an outlook makes it possible to predict the proper input settings which achieved a desired process output by designing various senarios for process set up. This approach was applied in Tile industry for spray dring process and in order to indicate the achieved improvement,three models:(i) regression model of process using multiple linear regression,(ii)Neural model of... 

One technique to reduce variance of output in comparing two or more systems via simulation is random number synchronization. the primary technique for achieving synchronization is to assign an independent seed to each random process and then use the same collection of seeds across all systems . Another way of synchronization in systems with limited customer population is to assign different seed to each customer (transaction) and then use the same collection of seeds across all systems. The main Question to be considered here is which of these methods of synchronization can better reduce variance of output in a queue with finite customer population  

This thesis presents a method to solve a redundancy allocation problem for the series-parallel system. The modeling formulation deals with the choice of the best redundancy strategy, component and redundancy level for each subsystem in order to maximize the system reliability under system-level constraints. Majority of the solution methods for the general redundancy allocation problems assume that the failure rate of components is determined. However, in practice variable failure rate may be used. The complexity of this problem is known as NP-hard and therefore the optimal solution is not accessible in the normal course of events. It is demonstrated in this thesis that genetic algorithm is... 

Sampling is so deep-rooted in our habits that it usually takes place unconsciously. A large number of books and articles have been published in this field. The connection between sampling and quality control is the reason that many industries have focused their attention on sampling; however, only a few numbersare familiar with bulk material sampling related issues. Describing this theory along with its seven errors is the main object of this research. Using this theory, characteristics of the lot of interest was analyzed. Creating necessary conditions for assuring sampling correctness is very critical and if these conditions cannot be provided, implementing some part of the theory issues... 

In this thesis we will provide a comprehensive study of process capability indices, and we use multivariate g-and-h Tukey distribution for calculating process capability indices of multivariate non-normal processes. Univariate process capability indices have been used commonly in literature for measuring the capability of a process. However, there are several processes with more than one quality characteristic. When these characteristics are independent, we can use univariate process capability indices, but when the characteristics are dependent we should use multivariate methods for measuring process capability. There have been several studies about multivariate process capability indices,... 

In some statistical process control applications, quality of a process or product 1s characterized by a relationship between a response variable and one or more explanatory variables which is referred to as profile by researchers. In some applications such as calibration, this relationship is characterized by a simple linear regression. However, in some situations, more complicated models are needed. It seems that there is a little attention to monitoring of profiles with binary response variables. Furthermore, the extensive applications of binary response variables in real industrial worlds make it necessary to concentrate on this kind of profiles. In this ... 

In this work, we propose a metamodel-based simulation optimization algorithm using a novel hybrid sequential experimental design. The algorithm starts with a metamodel construction phase in which at each stage, a sequential experimental design is used to select a new sample point from the search space using a hybrid exploration-exploitation search strategy. Based on the available design points at each stage, a metamodel is constructed using Artificial Neural Network (ANN) and Kriging interpolation techniques. The resulting metamodel is then used in the optimization process to evaluate new solutions. We use Imperialist Competitive Algorithm (ICA) which is a powerful population-based... 

This work attempt to analyze the impact of changes in nurse scheduling on quality of services at emergency department of Emam Khomeini Hospital Complex. In nurse scheduling some constraints such as maximum working hours per week and unacceptable working sequences must be considered. A simulation model is developed to cover the complete flow for the patient through the emergency department. Emergency department of Emam Khomeini is simulated in order to obtain the patient average waiting time for each nurse roster. Then a genetic algorithm is integrated with the simulation model. In each iteration genetic algorithm produces many nurse rosters . For each roster the patient average waiting time... 

Many simulation optimization problems are defined in random settings and their inputs have uncertainty. Therefore, in defining an optimal solution for these problems, uncertainties should be taken into account. The primary way of dealing with this , is Robust Optimization which finds solution immune to these changing settings. Aiming at finding a new approach for simulation optimization problems, this study investigates these uncertainties and robust methods. In the optimization problem, the goal and constraints are considered with separate risk measures and a related problem is defined as follows: Minimizing the weighted sum of all risks subject to the problem constraints. To solve the... 

Control charts are the most popular Statistical Process Control tools used to monitor process changes. However, they are not capable of identifying the real time of a process change, which is essential for diagnosing assignable causes of the change. Therefore, a number of methods of change-point estimation have been developed. In the literature, relatively little study has been done on multiple changes. In this research, a new method based on Maximum Likelihood Estimator (MLE) is introduced to identify linear drifts and step changes in multivariate multiple linear profiles. Due to the massive increase in the amount and time of the calculations along with the growth of the number of the... 

Before a construction project gets under way an attempt is made to examine different ways and scenarios for its implementation. Through such a process the more appropriate scenarios should be selected based on several criteria that are not necessarily at the same level in terms of importance. The purpose of this study is to examine different scenarios for implementing operations in the pre-construction phase of a project, based on several competing criteria with different importance levels in order to achieve a more efficient execution plan. This paper presents a new framework that integrates discrete event simulation (DES) and data envelopment analysis (DEA) to rank different scenarios for... 

Sampling is the process of selecting and analyzing part of population and generalizing the results to estimate characteristics of the population. Time and cost considerations or the destructive nature of experiments are the main reasons why we study a sample instead of the whole population. In typical applications, sampling units are well-defined which means these units can be defined, selected and analyzed separately. This is the case in taking samples from a human population or products that consist of distinct units. If sampling units are not well-defined, as in the case of a bulk material (e.g., a pile of dust or other particulate materials, a tankful of liquid, the air or other gases)... 

In many cases even high-quality products cannot satisfy the customer needs and this leads to having a lower share of the market. To achieve this purpose, customer satisfaction and robust design are regarded simultaneously to achieve a better quality. Balance Score Card (BSC) is proposed as a technique that could potentially has a great improvement effect on customer satisfaction. Moreover, with a non-linear programming (NLP), a novel method for integrating RSM and BSC have been proposed to accede robustness in design. The opinions of the customers are regarded in every system design, parameter design and tolerance design. To validate the applicability of the proposed approach, the approach... 

Control charts are one of the strongest optimization tools. Control charts issue warning due to out of control processby recorded data. As soon as charts warn, attempt start to find the changes reason.Finding out the issue on time save a lot of time and cost. By determining the time of this change, finding out the problem reason get faster. The real time of process change called change point. There exist many papers in change point field finding real time of change in literature. Each one considers the problem with specific assumptions. These assumptions consist of distribution function, change type, parameters and solution procedure. One kind of existing papers are about to determine normal... 

In this research, an integrated location-inventory-transportation problem with uncertainty in the parameters is analyzed using Robust Optimization techniques. Unknown demand distribution is the underlying assumption, which relates better to the reality. The model’s main purpose is to determine the number and locations of the Distribution Centers (DC) that connect the supplier to the retailers, and then to assign retailers to them. The problem’s mathematical model is developed on the basis of Robust Optimization techniques and the solution space is explored by Tabu Search. The results show that the Tabu Search method achieves optimality in small-scale cases, while providing desirable... 

Nowadays, credit risk is recognized as the most significant factor of bankruptcy in banking industry. Incorrect selection and unsuitable appropriation of financial resources to customers cause this risk. On the other hand, the detection of company operating and financial difficulties is a subject which has been fundamentally discussed in financial ratio analysis. As a result, this study tries to analyze existence and relationship between financial ratios of recipients and their reimbursement ability by evaluation of their conditions in awarding them credit. Furthermore, according to the credit risk context, some of financial ratios are selected and their values are obtained as the input... 

This study was conducted at one of the leading manufactures of detergents and hygienic products in Iran. It is a common practice there to repair equipments after they have breakdown therefore there is not much preventive maintenance tasks done there in spite of contracting out maintenance and preventive maintenance plans which are distributed every month to technical departments. As today competitive pressures have increased by imported commodities and difficulty in buying new machines, companies should learn how to revive their businesses and exploit equipment efficiently to reduce the high level of capital associated with equipment malfunctions. One of the methodologies applied world wide... 

Following the recent developments in the field of decision making, a considerable number of problems involved with stochastic systems can be thought of whose analysis depends on a set of intricate mathematical relations. In such cases, simulation is one of the most popular tools that can be applied toward analysis of behavior of such stochastic systems. Not only does not the simulation model rely on such intricate mathematical relations, it also enjoys the added advantage of being free of any restricting assumptions which may normally be considered in a stochastic system.To analyze such problem, one may aim at determining the best combination of input variables to optimize the system... 

In this thesis we propose a new metamodel based simulation optimization algorithm using sequential design of experiments. The main objective is to have a new method which can be used without deep knowledge of different kinds of metamodels, optimization techniques and design of experiments. The method uses three metamodels simulataneously and gradually adapts to the best metamodel. In each iteration, some points are chosen as candidates for future simulation. These points are ranked based on the quality of metamodel prediction and their placement among simulated points, the best point will be chosen for simulation. Comparing the proposed algorithm with some of the popular simulation... 

This research studies multi-objective master production schedule (MPS) and advanced order commitment (AOC) in two-stage supply chains. Simulation-based experimental analysis evaluates the impact of environmental and MPS design factors on schedule cost and instability. The results provide insight into multi-objective MPS design considerations through rolling schedule policies. The study reveals that the manufacturer's production smoothness utility coefficient and its interaction with other experimental factors considerably impact the system's performance. In addition, it introduces a simulation framework with embedded mixed integer programming models that could be used as a framework for...