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Endüstri Mühendisliği Yüksek Lisans Programı

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  • Program tanımları
    PROGRAM ÖZELLİKLERİ

    Endüstri Mühendisliği Yüksek Lisans programı, İngilizce ve tezli bir programdır. Program toplam 21 kredilik 7 ders, seminer dersi ve yüksek lisans tezinden oluşur; en erken 3 yarıyılda tamamlanabilir.

    PROGRAMIN AMAÇLARI VE HEDEF KİTLESİ

    Endüstri Mühendisliği Yüksek Lisans Programının amacı gerek üretim gerekse hizmet sektöründeki işletmelerde ortaya çıkan problemleri etkin ve verimli bir şekilde çözmek için matematiksel sistemlerin tasarlanması, yönetiminin planlanması ve yönetilmesi için gerekli çağdaş mühendislik yönetimi, teknoloji yönetimi ve bilgi yönetimi bilgilerini kazandırmaktır. Bu program, öğrencilerde endüstriyel uygulamalara yönelik yaratıcı ve yenilikçi fikirlerin oluşmasını sağlayacaktır. Bu program tüm sektörlerdeki işletmelerin verimliliğini ve etkinliğini arttırmanın güvenli bir adresidir.
    Bu programa Endüstri Mühendisleri ve İşletme Mühendisleri katılabilir. Programımız, verdiği gece eğitimi ile, profesyonel hayatına ara vermeden Endüstri Mühendisliği Yüksek Lisansı yapmak isteyen adaylara iyi bir imkan sunmaktadır. Öğrencilerimiz, yöneylem araştırması, üretim  yönetimi, hizmet sistemleri yönetimi, kalite yönetimi, bilgi yönetimi, sistem simülasyonu, proje yönetimi ve benzeri konularda detaylı araştırma yaparak yüksek lisans tezi hazırlayabilirler.

    Farklı mühendislik disiplinlerinden gelen adayların bu bölüme kabul edilmeleri için, kendi mühendislik disiplinlerinin özelliklerine göre belirli bir süre (bir veya iki semester) bilimsel hazırlık dersi almaları gerekmektedir.

    PROGRAM YAPISI

    Endüstri  Mühendisliği Yüksek Lisans programında, Endüstri Mühendisliği temel derslerinin yanı sıra yapılacak yüksek lisans tezini destekleyecek şekilde başka programlardan da ders alınabilir. Programa katılan herkesin alması gereken seminer dersi ve tamamlanması gereken yüksek lisans tezine ek olarak, öğrenciler kısıtlı ders havuzundan üç, bölüm seçmeli ders havuzundan iki, ve serbest seçmeli ders havuzundan iki ders alırlar. Bölüm seçmelileri havuzu, öğrencilerin kısıtlı seçmeliler havuzundan seçmedikleri dersler ve bunların haricinde açılmış alana özgü derslerden oluşur. Serbest seçmelilerse, Fen Bilimleri ve Sosyal Bilimler Enstitüsü tarafından açılan ve katılımcının çalışma alanı ve tez konusuyla ilgili olduğu düşünülen derslerin arasından seçilir.

    Required Courses

    Seminar   
    Master Thesis   

    Restricted Elective Courses (any three of the following)

    Applied Linear Algebra    
    Advanced Quality Management    
    Mathematical Programming and Modeling
    Project Management in Engineering
    Strategic Management Applications

    Departmental Electives

    Advanced Quality Management    
    Mathematical Programming and Modeling    
    Project Management in Engineering    
    Strategic Management Applications    
    System Simulation 
    Modeling and Analysis of Manufacturing Systems
    Sequencing and Scheduling    
    Advanced Optimization Techniques
    Design of Experiments    
    Case Studies in Industrial Engineering    
    Technology Management
    Lean Production    
    Product Development and Process Management    

    Advanced Quality Management
    Tools and techniques used in total quality management including quality function deployment (QFD), failure modes and effects analysis (FMEA), design of experiments (DoE), Statistical Process Control (SPC) and additional SPC techniques for variables (eg. multi-vari chart and short-run SPC), 5 S, Poka Yoke, service quality framework and SERVQUAL.

    Mathematical Programming and Modelling
    Large scale modeling approach, modeling and solution technique in linear programming, sensitivity analysis in linear programming, dynamic programming, nonlinear systems and modeling and solution technique, meta heuristic tools and their applications.

    Project Management in Engineering
    Project organization, project leader specification, engineering project design, create project network, project network techniques: CPM and PERT, budgeting, cost analysis, project management, implementation and control.

    Strategic Management Applications
    The field of strategic management examines how organizations (both for-profit companies and not-for profit agencies) gain sustainable competitive advantages systematically and consistently. To be successful, the organization?s strategy must permeate all departments and functional areas. As such, this course integrates knowledge and skills gained from various studies in the functional areas of business. In drawing on these tools, a general management point of view will be applied.

    Strategic Human Resource Management

    The value of human capital management, human capital management as strategic partner in organization, modeling and measurement of human capital, intangible asset management in organization.

    System Simulation
    Introduction to simulation systems, single server queuing systems, modeling approach in simulation, simulation with ARENA, techniques for increasing model, validity and credibility, validate the output from the model, simulation of manufacturing systems.

    Modelling & Analysis of Manufacturing Systems
    Manufacturing systems and models, Assembly lines, Line balancing, Transfer lines and serial systems, Shop scheduling with many products, Flexible manufacturing systems, and group technology.

    Sequencing & Scheduling
    Deterministic models: single MC, parallel MC; flow shops and flexible flow shops; single MC, parallel MC, flow shops and flexible flow shops, open shops, genetic algorithms, TABU search, simulated annealing, beam search, hill-climbing.

    Advanced Optimization
    Heuristic techniques such as genetic algorithm, ant colony, simulated annealing, TABU search and their applications, applied stochastic process and fuzzy logic.

    Design of Experiments

    Principles of experimental design: randomization, blocking, transformations, fixed and random effects. Single factor experiments (analysis of variance), Latin squares, factorial designs, response surface methods and designs, applications of advanced experimental design.

    Case studies in industrial engineering
    Modeling large scale projects; large scale project and applications in Industrial Engineering using with optimization, simulation, statistical and project management techniques.

    Principles of Engineering Management
    The practice of management as applied within technical organizations. Capitalism and opportunity; competitive advantage; creating a strategy; technology, innovation and timing; the technology entrepreneur; risk, return, and product design; corporate technology ventures; knowledge and learning; legal formation and intellectual property; marketing and sales; new enterprise organization; resource acquisition, organization and management; operations management; leadership.

    Statistical Data Analysis & Decision Making
    Emphasize the use of statistics as a tool for the analysis and interpretation of data. Understand how to collect and analyze data effectively and efficiently and how to draw appropriate conclusions from data to make a decision.

    Investment Decision Making
    Survey of material relevant to financial decision making for engineering activity, traditional engineering economy topics, fundamentals of accounting and financial planning, budgeting, and estimating.

    Decision Analysis
    Students integrate scientific evidence, patients' preferences, and experts' opinions to analyze managerial decisions and identify optimal alternatives. Included are applications to analysis of practice patterns, benchmarking, probabilistic risk assessment, cost analysis, conflict analysis and measurement of severity of illness. Decision analytical tools such as multi-attribute value models, Bayesian probability networks, and decision trees are covered.

    Technology Management
    Strategic management of technology and innovation, developing a licensing strategy, proper valuations of intellectual property, gathering and utilizing market research, marketing technology, negotiating and drafting licensing agreements, the legal hurdles, operational needs, and strategies involved.

    Quality Management
    Quality and quality system concepts in business, statistical quality control, statistical process control, quality assurance system and ISO 9000, quality function organization, quality deployment function, FMEA, 6-Sigma and its applications.

    Business Management & Enterpreneurship
    This course explains the stages of the development of technological innovations starting from a research project into establishing a business. Research and development, engineering project management, management of intellectual property, patenting, venture capital, industrial incubation, licensing, product development, outsourcing, and establishment of marketing and sales channels will be among the major topics of the course. The students will develop a business plan for their hypothetical technological innovation.

    Human Resources Management
    Requirement and selection system, performance management, award and compensation system, manpower planning system, employee relations, the analysis and design of work, training, employee development.

    Risk Management
    Objectives of risk management, demand for risk management (utility theory), analyzing tools, legal liability, risk retention/reduction, financial risk management, futures and options, enterprise risk management.

    Service Operations Management
    The role of services in an economy, nature of services, market positioning, service strategy, new service development, creating a service culture, the service encounter, e-service, service quality, quality improvement and productivity, location and layout: supporting facility, managing supply and demand, yield management, managing waiting lines, managing service supply relationships, growth and globalization of service.

    Lean Production
    Statistical methods useful in quality improvement; develop a broad understanding of lean production principles and practices; build capability to implement lean production initiatives in manufacturing operations; operate with awareness at the enterprise level.

    Product Development& Process Management
    Explores the methodology for managing the cohesive development and marketing of new products from idea inception to product discontinuation. Emphasis is placed on product development and support and market analysis in both traditional and entrepreneurial company settings. Concurrent engineering, reengineering, lean production processes.

    Applied Optimization Techniques

    Advanced Excel applications, model building, sensitivity analysis; applied linear programming models, pricing applications, DEA and its applications.

    Supply Chain& Logistics Management

    A systems approach to managing the entire flow of information, materials, and services from raw materials suppliers through factories and warehouses to the end customer, topics: Building blocks of a supply chain network, performance measures, decisions in the supply chain world, models for supply chain decision-making; relation to ERP, inventory management, e-logistics.

    Operations Management
    As a primary business function, along with marketing and finance, the operations function provides goods and services directly to the company's customers. Through models, methods, this course explores how the operations function plays a vital role in achieving a company's strategic plans and is a major determinant of a company's financial performance. Forecasting, design, inventory management, facilities planning, location, and supply chain issues.

    Customer Relationship Management
    Basic theories and methodology of customer relationship management, including identifying profitable customers, understanding their needs and wants, and building a bond with them, by developing customer-centric products and services directed toward providing customer value. Hands-on experience with popular analytical CRM and data mining tools that are widely used in the industry. Issues in the customer life cycle: market segmentation, customer acquisition, basket analysis and cross-selling, customer retention and loyalty, and practical issues in implementation of successful CRM programs.

    Seminar

    Master Thesis

    Project

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