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Transient liquid phase bonding of dual phase steels using Fe-based, Ni-based, and pure Cu interlayers
, Article Journal of Manufacturing Processes ; Volume 30 , 2017 , Pages 106-115 ; 15266125 (ISSN) ; Ekrami, A ; Sharif University of Technology
2017
Abstract
Transient liquid phase (TLP) bonding is a joining process which combines benefits of diffusion bonding and brazing. Therefore, this method has widely been used in joining of materials which are sensitive to fusion welding. Interlayer composition, as one of the most important factors of TLP bonding, can affect the bonding region composition, microstructure, and hence mechanical properties of the joint. In this research, Fe-based, Ni-based, and commercially pure Cu interlayers are used to bond low-carbon steel components which are then heat treated to produce dual phase steel. The present work focuses on two main goals. Firstly, drawing a comparison of microstructure and mechanical properties...
The Effect of Interlayer Composition on Microstructure and Mechanical Properties of Transient Liquid Phase Bonded Dual Phase Steels
, M.Sc. Thesis Sharif University of Technology ; Ekrami, Ali Akbar (Supervisor)
Abstract
Interlayer composition as one of the most important factors of TLP bonding could affect bonding region composition and microstructure that both of them govern the mechanical properties of the joint. Due to the risk of substrate microstructure degradation , welding of dual phase steel needs more cautions. TLP bonding ideally acquires joints having more similar microstructure to substrate. Moreover , using this method could avoid the change of base metal microstructure when heat treatment of carbon steel is postponed until after bonding. Fe-based , Ni-based and commercially pure Cu are three different composition has been studied in this work. The bonded samples were investigated by optic and...
A Process Mining Approach to Analyze Customer Journeys to Improve Customer Experience
, M.Sc. Thesis Sharif University of Technology ; Hassannayebi, Erfan (Supervisor)
Abstract
With the growth of the number of online service providers and the need to innovate in these services, in this study, the processes and the journeys taken by visitors of a website that provides employment services and employment insurance has been analyzed. In this research, process mining techniques and predictive process monitoring were implemented. With the use of a supervised and unsupervised learning algorithm, it attempted to identify the customer journeys' output and the existing patterns that lead to the complaint. In the first step, the website event log is extracted. Afterward, by using frequency-based encoding methods, the journeys traveled by users were clustered based on the...
Predictive Business Process Monitoring Using Machine Learning Algorithms
, M.Sc. Thesis Sharif University of Technology ; Hassannayebi, Erfan (Supervisor)
Abstract
In order to survive in today's business world, which is changing at a very fast pace, organizations can detect deviations even before they occur, quickly and with a high percentage of confidence, by analyzing their processes, in order to prevent disruptions in the processes. by monitoring the information systems that automatically execute business processes, it is possible to ensure the correct implementation of the existing processes. For this purpose, various techniques for monitoring business processes have been presented so that managers have a comprehensive and real view of how implement processes and be able to identify possible deviations in the future and try to fix them because the...
Data-Driven Prediction for Monitoring Business Process Pperformances Based on Classification Algorithms
, M.Sc. Thesis Sharif University of Technology ; Hassannayebi, Erfan (Supervisor)
Abstract
In recent years, several studies have been conducted in the field of data mining techniques in the field of process mining with the aim of improving the performance of organizations. Predictive process monitoring is a data-driven approach that helps business managers to improve the status and conditions of their organization. In this approach, the event log, which includes a set of completed examples of a process, is received as input, and machine learning methods are used to predict the outcome and results of the organization's processes before the process is completed. This prediction can include the prediction of the final result, the next event, the time remaining until the completion of...
Operations Optimization in Supply Chain Systems using Simulation and Reinforcement Learning
, M.Sc. Thesis Sharif University of Technology ; Hassan Nayebi, Erfan (Supervisor)
Abstract
The inventory costs constitute a significant portion of the supply chain costs. Therefore, choosing an optimal inventory policy for orders is of great importance. The aim of this research is to find the optimal inventory policy for a distribution center in a three-tier supply chain consisting of a manufacturer, a distribution center, and a retailer. This research simulates a supply chain in agent-based framework and optimizes it using reinforcement learning. The optimization KPI in this research is the mean daily cost of the supply chain. Finally, the result obtained from reinforcement learning is compared with the optimized result of AnyLogic and the mean daily cost in the model optimized...
A System Dynamic Simulation Approach to Investigate Economic And Environment Factors Based on VUCA framework: A Case Study in Petrochemical Industry
, M.Sc. Thesis Sharif University of Technology ; Hassannayebi, Erfan (Supervisor)
Abstract
To maintain adaptability, businesses should anticipate changes in their environment. The commonly employed forecasting method within corporate circles is the bottom-up approach, which relies on historical data for projecting future trends. However, research suggests that this approach often falls short of accurately reflecting real-world events. This has led to the adoption of dynamic systems modeling, a technique grounded in the assumption of stable conditions. This method effectively replicates the system's current state, thereby assisting in predicting future behaviors over a longer timeframe. The dynamic systems modeling approach was employed in this study, underscoring the imperative...
Discovering and Improving the Processes of an Iranian Psychiatric Hospital Using Process Mining
, M.Sc. Thesis Sharif University of Technology ; Hassan Nayebi, Erfan (Supervisor)
Abstract
Providing quality hospital services depends on the efficient and correct implementation of processes. Therapeutic care processes are a set of activities that are carried out with the aim of diagnosing, treating and preventing any disease in order to improve and promote the patient's health. The purpose of this study is to use process mining techniques to discover and improve healthcare processes. The case study of this research is a psychiatric hospital in Shiraz. The approach implemented in this research consists of three main stages including data pre-processing, model discovery phase, and analysis phase. Three algorithms including Heuristic Miner, Inductive Miner, and ILP Miner were used...
The investigation of natural super-cavitation flow behind three-dimensional cavitators: Full cavitation model
, Article Applied Mathematical Modelling ; Volume 45 , 2016 , Pages 165-178 ; 0307904X (ISSN) ; Kadivar, Erfan ; Javadi, K ; Javadpour, S. M ; Sharif University of Technology
Elsevier Inc
2016
Abstract
In this study, natural super-cavitating flow around three different conical cavitators with wedge angles of 30°, 45° and 60° is investigated. We apply the k−ϵ turbulence model and the volume of fluid (VOF) technique to numerically study the three-dimensional cavitating flow around the cavitators. The turbulence approach is coupled with a mass transfer model which is implemented into the finite-volume package. Simulations are performed for different cavitation numbers. Finally, the effects of some important parameters such as the cavitation index, inlet velocity, Froude number and wedge angle of cavitators on the geometrical characteristics of the super-cavities are discussed. Our numerical...
Improve Performance of Process Mining Algorithms in Low-Level Event Log with Machine Learning Methods
, M.Sc. Thesis Sharif University of Technology ; Hassan Nayebi, Erfan (Supervisor)
Abstract
This thesis abstract addresses the use of process mining techniques when event data is stored at varying levels of granularity. While most techniques assume that events have the same level of granularity, real data is often stored differently. Pre-processing techniques allow for appropriate summarization of the data, which simplifies the output while retaining important process details. The goal is to ensure an interpretable output for stakeholders and different business teams without losing critical process points. However, adding new data as a feature to the dataset can be expensive, and at times, infeasible. Therefore, existing data is the only solution. To overcome this challenge, this...
Estimating Evaporation from Non-Agricultural Areas (Bare Soil and Range Land) in the Lake Urmia Basin
,
M.Sc. Thesis
Sharif University of Technology
;
Tajrishi, Masood
(Supervisor)
;
Jalilvand, Ehsan
(Co-Supervisor)
;
Haghighi, Erfan
(Co-Supervisor)
Abstract
Evaporation is one of the main parameters of the mass transfer from earth to the atmosphere, which annually transfers more than 65 billion cubic meters of water. Worldwide, evaporation consumes 25% of the energy input and plays a key role in restoring 60% of the precipitation to the atmosphere. Small changes in the water budget and evapotranspiration (ET) in arid and semi-arid areas can cause a large change in ecosystem health. Lake Urmia Basin has been taken into huge consideration due to steepest decline in lake level in the last three decades. Estimating evapotranspiration of this basin is important for the study of agricultural water consumption, hydrological modeling, water resources...
Geomechanical Analysis of Wellbore Instability in Kupal Oil Field
, M.Sc. Thesis Sharif University of Technology ; Khoei, Amir Reza (Co-Advisor) ; Erfan Nia, Ali (Co-Advisor) ; Shad, Saeed (Supervisor)
Abstract
The wellbore instability is one of the challenging problems in the oil industry, which entails huge costs for the industry every year. This phenomenon not only causes numerous problems in drilling and completion of wells, but also reduces production and loss of wells. In recent years, this problem has become much more serious in the Kupal oilfield. As a result, a large number of wells drilled in the field shortly after completion face with the problem of instability, integrity and casing collapse. According to the studies, one of the main causes of such a problem is the Gachsaran high pressure formation. Despite the complexity and importance of this issue, there is not a comprehensive study...
Synthesis and characterization of N- diethyl methyl chitosan
, Article Iranian Polymer Journal (English Edition) ; Volume 13, Issue 5 , 2004 , Pages 431-436+437 ; 10261265 (ISSN) ; Mahdavinia, G ; Sadeghi, A. M ; Erfan, M ; Amini, M ; Tehrani, M. R ; Shafiee, A ; Sharif University of Technology
2004
Abstract
Biodegradable polymers such as chitosan have been used extensively in biomedical fields in the form of sutures; wound dressing and as artificial skin. Colonic drug delivery for either local or systemic effects has been the subject of much research over the last decade. Chitosan exhibits poor solubility at pH values above 6 that prevent enhancing effects at sites of absorption of drugs. In the present work, N-diethyl methyl chitosan (DEMC) was prepared based on a modified two-step process via a 22 factorial design to optimize the preparative conditions. DEMC Polymer with different degrees of quaternization for pharmacological and pharmaceutical experiments was achieved. The reaction was...