INDUSTRIAL ENGINEERING MSc PROGRAMME First Year I. Semester Code Course Title ECTS T+P Credit C/E Language 501001101 7.5 3+0+0 3 C Turkish 503201503 7.5 3+0+0 3 C Turkish Elective Course-1 7.5 3+0+0 3 E Turkish Elective Course-2 7.5 3+0+0 3 E Turkish of I. Semester 30 12 II. Semester Code Course Title ECTS T+P Credit C/E Language Elective Course-3 7.5 3+0+0 3 E Turkish Elective Course-4 7.5 3+0+0 3 E Turkish Elective Course-5 7.5 3+0+0 3 E Turkish 503202001 Seminar 7.5 0+1+0 - C Turkish Total of II. Semester 30 9 OF FIRST YEAR 60 21 Second Year III. Semester Code Course Title ECTS T+P Credit C/E Language 503201702 MSc THESIS STUDY 25 0+1+0 - C Turkish 503201703 SPECIALIZATION COURSE 5 3+0+0 - C Turkish Total of III. Semester 30 IV. Semester Code Course ECTS T+P Credit C/E Language 503201702 MSc THESIS STUDY 25 0+1+0 - C Turkish 503201703 SPECIALIZATION FIELD COURSE 5 3+0+0 - C Turkish of IV. Semester 30 OF SECOND YEAR 60 Elective Courses Code Course Title ECTS T+P Credit C/E 503201514 7.5 3+0+0 3 E Turkish 7.5 3+0+0 3 E Turkish 503201510 7.5 3+0+0 3 E Turkish 503202512 7.5 3+0+0 3 E Turkish 503202501 7.5 3+0+0 3 E Turkish 503212604 7.5 3+0+0 3 E Turkish
Midterm 1 35 Quiz Homework Project 1 30 Report Seminar Other ) Final Examination 35 PREREQUISITE(S) SHORT COURSE CONTENT Manufacturing Resource Planning, Aggregate Planning, Master Production Sceheduling, MRP, CRP, JIT COURSE OBJECTIVES To introduce Manufacturing Resource Planning and related operations and to give information about how to do them. COURSE CONTRIBUTION TO THE PROFESSIONAL EDUCATION To teach which (and how) operations are performed for Manufacturing Resource Planning in a production environment. LEARNING OUTCOMES OF THE COURSE Ability to determine, define, formulate and complex engineering problems; for that purpose an ability to select and use convenient analytical and experimental methods TEXTBOOK Thomas E. Vollmann, William L. Berry, D. Clay Whybark, Manufacturing Planning and Control Systems, Irwin/McGraw-Hill, 1997, 4th edition REFERENCES Khalid Sheikh, Manufacturing Resource Planning (Mrp Ii): With Introduction to Erp, Scm and Crm, McGraw-Hill Professional Engineering Series, 2003
3.Montgomery, D. C. (1997) : Introduction to Statistical Quality Control, (3. bası), John Wiley & Sons, Inc., NewYork, 4.Burnak, N. (1997) : Toplam Kalite Kontrolu : İstatistiksel Süreç Kontrolu, Osmangazi Üniv.,TEKAM yayın no:TS-97-008-NB, Eskişehir, 5.Grant, E. L., Leavenworth, R. S. (1988) : Statistical Quality Control, (6. bası), McGraw-Hill, Inc. NewYork, 6.Tan, S., Peşkircioğlu, N. (1991) : Kalitesizliğin Maliyeti, Prodüktivite Merkezi, Yayın no: 316, Anakara, 7.Özenci, B. T. Cunbul, Ö. L. (1998): Kalite Ekonomisi, Türkiye Kalite Derneği Yayınları, No:2, İstanbul,
DEPARTMENT INDUSTRIAL ENGINEERING (MSc) SEMESTER COURSE CODE 503202509 TITLE Materials Handling and Warehouse Systems LEVEL HOUR/WEEK Credit ECTS TYPE LANGUAGE Theory Practice Laboratory MSc 3 0 0 3 7.5 COMPULSORY ( ) ELECTIVE ( X ) Turkish CREDIT DISTRIBUTION Basic Science Basic Engineering Knowledge in the discipline [if it contains considerable design content, mark with ()] ASSESSMENT CRITERIA SEMESTER ACTIVITIES Evaluation Type Number Contribution ( % ) Midterm 1 30 Quiz Homework Project 1 30 Report Seminar Other ) Final Examination 40 PREREQUISITE(S) Facilities Planning, Simulation, and Engineering Economics courses should be taken COURSE CONTENT Materials handling equipments, handling systems, principles, analysis of, conveyors, AGV, AS/RS and carousel systems, warehouse models, warehouse design and management, relations, special topics in materials handling. COURSE OBJECTIVES Main aim of the course is to introduce the basic terminology and techniques of materials handling and warehouse systems and their influence to the production in terms of efficiency and efficacy. To relate the new developments, current techniques and operations research. COURSE CONTRIBUTION TO THE PROFESSIONAL EDUCATION LEARNING OUTCOMES OF THE COURSE 1.Understand the materials handling systems that are crucial for manufacturing systems and current techniques and metodologies, 2.Apply operations research principles to solve and design materials handling systems 3.Assessing manufacturing systems in terms of efficiency and effectiveness by considering new handling equipments, 4. Analyzing costs related with new purchase of equipments, renwals, and maintenance costs. TEXTBOOK 1.Askin R.G., Standrigge, 1993, Modelling and Analysis of Manufacturing Systems, John Wiley & Sons, Inc. 2.Garcia-Diaz A., Smith J.M., 2008, Facilities Planning and Design, Pearson Prince Hall.
COURSE SCHEDULE (Weekly) WEEK TOPICS 1 Basic concepts of integer programming 2 Using 0-1 integer variables and ensuring special conditions 3 Models of knapsack, transportation, assignment, matching and bottleneck type problems. 4 Models of network and routing problems 5 Models of set covering, p-median, p-center, facility layout and scheduling problems 6 Midterm Examination 1 7 Complexity, concets of P, NP, NP-hard and total unimodularity 8 Enumeration, rounding and dynamic programming techniques 9 Branch and algorithm 10 Additivie algorithm, cutting algorithm and some special heuristic algorithms 11 Midterm Examination 2 12 Column generation and solution of cutting problems 13 Tightening of a and branch and cut algorithm 14 Tabu search and simulated annealing algorithm 15,16 Final Examination CONTRIBUTION OF THE COURSE LEARNING OUTCOMES TO THE INDUSTRIAL ENGINEERING PhD PROGRAM LEARNING OUTCOMES CONTRIBUTION LEVEL NO LEARNING OUTCOMES (PhD) 3 High 2 Mid 1 Low LO 1 Ability to understand and implement mathematics, basic and engineering sciences at utmost level in the field of Industrial Engineering and other relevant fields. LO 2 Ability to the newest knowledge, design, plan, manage, finalize and implement original research processes bringing innovation to science or technology in the field of Industrial Engineering and other relevant fields. LO 3 Ability to design, plan, manage, finalize and implement multidisciplinary innovative studies LO 4 Ability to present and publish the results of academic studies at all kind of platforms. LO 5 Ability to use at least one language sufficiently, skills for written, verbal, visual communication and discussion in that language. LO 6 Ability to make evaluation, critical analysis and synthesis about conceptions that are generated in the relevant field. LO 7 Ability to evaluate actual scientific, technological, social, cultural and environmental developments besides awareness of scientific neutrality, ethics and responsibility. Prepared by : Assoc. Prof. Dr. Aydın Sipahioğlu Date: 18.06.2015 Signature: DEPARTMENT INDUSTRIAL ENGINEERING (MSc) SEMESTER COURSE CODE 503212603 TITLE Multiobjective Programming
LEVEL HOUR/WEEK Credit ECTS TYPE LANGUAGE Theory Practice Laboratory MSc 3 0 0 3 7.5 COMPULSORY ( ) ELECTIVE ( x ) Turkish CREDIT DISTRIBUTION Basic Science Basic Engineering Knowledge in the discipline [if it contains considerable design content, mark with ()] x ASSESSMENT CRITERIA SEMESTER ACTIVITIES Evaluation Type Number Contribution ( % ) Midterm 1 20 Quiz Homework 1 10 Project 1 40 Report Seminar Other ) Final Examination 30 PREREQUISITE(S) SHORT COURSE CONTENT Multiobjective programming examples, Decision and Objective Space, Order Cones, Efficient and nondominated solutions. Scalarization Methods, Nonscalarizing Methods. Solving multiobjective programming models by using software such as Lingo or Gams and interpretation of solution reports. COURSE OBJECTIVES The main aim of this course is to give information about fundamentals of multiobjective programming and solution techniques of multiobjective programming. COURSE CONTRIBUTION TO THE PROFESSIONAL EDUCATION By the end of this module students will be able to modeling and solving of multiobjective programming problems by using LINGO or GAMS. They will also be able to interpret the solution reports. LEARNING OUTCOMES OF THE COURSE Notification the modelling and solving of multiobjective decision problems, application of modellling and solving of real life problems, comments of solution reports obtained by GAMS or LINGO, anayzing of different solution methods. TEXTBOOK Matthias Ehrgott, Multicriteria Optimization, Second Edition, Springer, 2005. OTHER REFERENCES Vira Chankong and Yacov Y.Haimes, Multiobjective Decision Making: Theory and Methodology, Elsevier Publishing, 1983.
COURSE SCHEDULE (Weekly) WEEK TOPICS 1 Introduction to Genetic and Evolutionary Algorithms 2 Classic Optimization Problems 3 Classic Genetic Algorithms 4 Mathematical Models of Genetic Algorithms 5 Evolutionary Programming 6 Midterm Examination 1 7 Evolutionary Strategies 8 Genetic Programming 9 Types of Evolutionary and Genetic Algorithms I 10 Types of Evolutionary and Genetic Algorithms II 11 Midterm Examination 2 12 Combinatorial Optimization 13 Restricted Optimization 14 Multiobjective Optimization 15,16 Final Examination CONTRIBUTION OF THE COURSE LEARNING OUTCOMES TO THE INDUSTRIAL ENGINEERING PhD PROGRAM LEARNING OUTCOMES CONTRIBUTION LEVEL NO LEARNING OUTCOMES (PhD) 3 High 2 Mid 1 Low LO 1 Ability to understand and implement mathematics, basic and engineering sciences at utmost level in the field of Industrial Engineering and other relevant fields. LO 2 Ability to the newest knowledge, design, plan, manage, finalize and implement original research processes bringing innovation to science or technology in the field of Industrial Engineering and other relevant fields. LO 3 Ability to design, plan, manage, finalize and implement multidisciplinary innovative studies LO 4 Ability to present and publish the results of academic studies at all kind of platforms. LO 5 Ability to use at least one language sufficiently, skills for written, verbal, visual communication and discussion in that language. LO 6 Ability to make evaluation, critical analysis and synthesis about conceptions that are generated in the relevant field. LO 7 Ability to evaluate actual scientific, technological, social, cultural and environmental developments besides awareness of scientific neutrality, ethics and responsibility. Prepared by : Prof.Dr. Muzaffer KAPANOĞLU Date: 03.11.2015 Signature: DEPARTMENT INDUSTRIAL ENGINEERING (MSc) SEMESTER COURSE CODE 503201510 TITLE Decision Support Systems and Expert Systems
COURSE SCHEDULE (Weekly) WEEK TOPICS 1 Decision Support Systems and Business Intelligence 2 Decision-Making Systems, Modeling and Support 3 Decision Support Systems: Concepts, Methods, Technologies 4 Modeling and Analysis 5 Business Intelligence and Data Warehousing 6 Midterm Examination 1 7 Business Analytics 8 Data Visualization 9 Data Mining 10 Web Analytics 11 Midterm Examination 2 12 Business Performance Management 13 Knowledge Management 14 Expert Systems 15,16 Final Examination CONTRIBUTION OF THE COURSE LEARNING OUTCOMES TO THE INDUSTRIAL ENGINEERING MSc PROGRAM LEARNING OUTCOMES CONTRIBUTION LEVEL NO LEARNING OUTCOMES (MSc) 3 High 2 Mid 1 Low LO 1 Accessing deep and advanced knowledge through scientific researches in the field of Industrial Engineering, ability to evaluate, interpret and implement the knowledge. LO 2 Having comprehensive knowledge actual techniques and methods in engineering as well as their constraints. LO 3 Completion and implementation of uncertain, limited or missing data through scientific methods in addition ability to use knowledge belongs to various disciplines. LO 4 Awareness of new and developing Industrial Engineering practices, ability to investigate and learn them as needed. LO 5 Ability to define and formulate problems related to industrial engineering and skills for developing methods to solve the problems and using innovative methods during solutions. LO 6 Developing new and/or original methods and conceptions; ability to design systems or processes and ability to develop innovative solutions in designs. LO 7 Ability to work efficiently in disciplinary and multidisciplinary teams, skills for taking the lead in the teams and developing solution approaches under complicate conditions; ability to work independently and take responsibility. LO 8 Ability to use a language for verbal and written communication. LO 9 Ability to transmit results and processes of studies systematically and definitively to national/international, verbal/written platforms are inside or outside the relevant field. LO 10 To be informed of social, environmental, health, security and law aspects of engineering practices besides project management and business life practices and awareness of constraints caused by them. LO 11 Awareness of considering social, scientific and ethical principles during data collection, interpretation, announcement stages besides all vocational activities. Prepared by : Prof.Dr.Muzaffer Kapanoğlu Date: 03.11.2015 Signature:
HOUR/WEEK Credit ECTS TYPE LANGUAGE Theory Practice Laboratory MSc 3 - - 3 7.5 COMPULSORY ( ) ELECTIVE ( X ) Turkish CREDIT DISTRIBUTION Basic Science Basic Engineering Knowledge in the discipline [if it contains considerable design content, mark with ()] X ASSESSMENT CRITERIA SEMESTER ACTIVITIES Evaluation Type Number Contribution ( % ) Midterm 2 50 Quiz Homework 1 15 Project Report Seminar Other ) Examination 35 PREREQUISITE(S) SHORT COURSE CONTENT Rewiev of basics of probability and statsitics; Reliability and system safety measures. Life distributions and applications in reliability. System reliability models. Design by reliability and probabilistic design. Reliability estimation and measurement by testing for binomial, exponential, and Weibull distributions; rewiev of reliability software.. COURSE OBJECTIVES To understand the theory and practice system reliability concepts and statistical methods in the area. COURSE CONTRIBUTION TO THE PROFESSIONAL EDUCATION To develop and promote research interest in applying system reliability concepts. LEARNING OUTCOMES OF THE COURSE 1. Application of probability and statistical methods; 2.To define and develop measures for reliability and safety 3. To model reliability by various life distributions 4. To be able to compute system reliability 5. To understand design and management of reliability programs TEXTBOOK E. E. Lewis, Introduction to Reliability Engineering, John Wiley & Sons, 1994. OTHER REFERENCES M. Bayazıt: Mühendislikte Güvenilirlik ve Risk Analizi; Birsen Yayınevi, 2007
COURSE SCHEDULE (Weekly) WEEK TOPICS 1 Evolution and definition of six sigma 2 Structure of six sigmas 3 Six sigma and quality improvement 4 Probability, and some important discrete and continuous distributions 5 Statistics and basics 6 Midterm Examination 1 7 Measurement system analysis 8 Descriptive statistics 9 Inferential statistics 10 Regression analysis 11 Midterm Examination 2 12 Analysis of variance 13 Analysis of variance 14 Acceptance sampling plans 15,16 Final Examination CONTRIBUTION OF THE COURSE LEARNING OUTCOMES TO THE INDUSTRIAL ENGINEERING MSc PROGRAM LEARNING OUTCOMES CONTRIBUTION LEVEL NO LEARNING OUTCOMES (MSc) 3 High 2 Mid 1 Low LO 1 Accessing deep and advanced knowledge through scientific researches in the field of Industrial Engineering, ability to evaluate, interpret and implement the knowledge. LO 2 Having comprehensive knowledge actual techniques and methods in engineering as well as their constraints. LO 3 Completion and implementation of uncertain, limited or missing data through scientific methods in addition ability to use knowledge belongs to various disciplines. LO 4 Awareness of new and developing Industrial Engineering practices, ability to investigate and learn them as needed. LO 5 Ability to define and formulate problems related to industrial engineering and skills for developing methods to solve the problems and using innovative methods during solutions. LO 6 Developing new and/or original methods and conceptions; ability to design systems or processes and ability to develop innovative solutions in designs. LO 7 Ability to work efficiently in disciplinary and multidisciplinary teams, skills for taking the lead in the teams and developing solution approaches under complicate conditions; ability to work independently and take responsibility. LO 8 Ability to use a language for verbal and written communication. LO 9 Ability to transmit results and processes of studies systematically and definitively to national/international, verbal/written platforms are inside or outside the relevant field. LO 10 To be informed of social, environmental, health, security and law aspects of engineering practices besides project management and business life practices and awareness of constraints caused by them. LO 11 Awareness of considering social, scientific and ethical principles during data collection, interpretation, announcement stages besides all vocational activities. Prepared by : Nimetullah BURNAK, Ph. D., Prof. Date: 21, 2016 Signature:
DEPARTMENT INDUSTRIAL ENGINEERING (MSc) SEMESTER COURSE CODE 5032xxxxx TITLE Personnel Evaluation LEVEL HOUR/WEEK Credit ECTS TYPE LANGUAGE Theory Practice Laboratory MSc 3 0 0 3 7,5 COMPULSORY ( ) ELECTIVE ( x ) Turkish CREDIT DISTRIBUTION Science Basic Engineering Knowledge in the discipline [if it contains considerable design content, mark with ()] 1 2 ASSESSMENT CRITERIA SEMESTER ACTIVITIES Evaluation Type Number Contribution ( % ) Midterm 1 30 Quiz Homework Project 1 20 Report Seminar Other ) Final Examination 50 PREREQUISITE(S) COURSE CONTENT resource management, definition, importance, factors forcing change in HRM, Job Analysis, job evaluation system process and methods, blue and white-collar job evaluation system, charge management, performance evaluation process and methods, personnel evaluation system design COURSE OBJECTIVES Explain the importance of Human Resource Management, labor motivation, give the ability to set up job evaluation and performance appraisal systems COURSE CONTRIBUTION TO THE PROFESSIONAL EDUCATION Gain the skills of how to set up valuation systems to in order to provide motivation and productivity of the labor skills LEARNING OUTCOMES OF THE COURSE 1. Ability to set up a business and / or performance appraisal system 2. Gain ethics of the protection of human rights with business and performance appraisal system TEXTBOOK Kahya, E., Personel (İş ve Performans) Değerlemesi, ESOGÜ Endüstri Mühendisliği Bölümü, 2016, Eskişehir. OTHER REFERENCES 1. Sabuncuoğlu, Z., İnsan Kaynakları Yönetimi, Ezgi Kitabevi, 2000, Bursa. 2. Acar, N., İnsan Kaynakları Yönetimi, MPM Yayın No: 640, 2000, Ankara.
COURSE SCHEDULE (Weekly) WEEK TOPICS 1 Resources Management (HRM) 2 Job analysis 3 Job evaluation 4 Point method 5 Blue-collar job evaluation system 6 Midterm Examination 1 7 White-collar job evaluation system 8 Salary management 9 Blue-collar salary system 10 Performance appraisal 11 Midterm Examination 2 12 Evaluation methods 13 Applicaions from some sectors 14 Personnel evaluation system 15,16 Final Examination CONTRIBUTION OF THE COURSE LEARNING OUTCOMES TO THE INDUSTRIAL ENGINEERING MSc PROGRAM LEARNING OUTCOMES CONTRIBUTION LEVEL NO LEARNING OUTCOMES (MSc) 3 High 2 Mid 1 Low LO 1 Accessing deep and advanced knowledge through scientific researches in the field of Industrial Engineering, ability to evaluate, interpret and implement the knowledge. LO 2 Having comprehensive knowledge actual techniques and methods in engineering as well as their constraints. LO 3 Completion and implementation of uncertain, limited or missing data through scientific methods in addition ability to use knowledge belongs to various disciplines. LO 4 Awareness of new and developing Industrial Engineering practices, ability to investigate and them as needed. LO 5 Ability to define and formulate problems related to industrial engineering and skills for developing methods to solve the problems and using innovative methods during solutions. LO 6 Developing new and/or original methods and conceptions; ability to design systems or processes and ability to develop innovative solutions in designs. LO 7 Ability to work efficiently in disciplinary and multidisciplinary teams, skills for taking the lead in the teams and developing solution approaches under complicate conditions; ability to work independently and take responsibility. LO 8 Ability to use a language for verbal and written communication. LO 9 Ability to transmit results and processes of studies systematically and definitively to national/international, verbal/written platforms which are inside or outside the relevant field. LO 10 To be informed of social, environmental, health, security and law aspects of engineering practices besides project management and business life practices and awareness of constraints caused by them. LO 11 Awareness of considering social, scientific and ethical principles during data collection, interpretation, announcement stages besides all vocational activities. Prepared by : Proff. Emin KAHYA Date: 18.04.2016 Signature:
DEPARTMENT Joint Course for the Institute SEMESTER Fall-Spring COURSE CODE TITLE The Scientific Research Methods and Its Ethics LEVEL HOUR/WEEK Credit ECTS TYPE LANGUAGE Theory Practice Laboratory MSc- Ph.D 3 0 0 3+0 7,5 COMPULSORY ( X ) ELECTIVE ( ) Turkish CREDIT DISTRIBUTION Science Basic Engineering Knowledge in the discipline [if it contains considerable design content, mark with ()] 1,5 1,5 ASSESSMENT CRITERIA SEMESTER ACTIVITIES Evaluation Type Number Contribution ( % ) Midterm 1 40 Quiz Homework Project Report Seminar ) Final Examination 60 PREREQUISITE(S) None SHORT COURSE CONTENT Science, the scientific thought and other fundamental concepts, the scientific research process and its techniques, Methodology: Data Reporting the scientific research (Preparation of a thesis, oral presentation, article, project), Ethics, Ethics of scientific research and publication. COURSE OBJECTIVES The main objectives are: To examine the foundations of scientific research and the scientific research methods, to teach the principles of both the methodology and the ethics, to realize the process on a scientific research and to evaluate the results of research, to teach reporting the results of research (on a thesis, presentation, article). COURSE CONTRIBUTION TO THE PROFESSIONAL EDUCATION Applying the scientific research methods and the ethical rules in their professional life. LEARNING OUTCOMES OF THE COURSE Gaining awareness on ethical principles at basic research methods, becoming skillful at analyzing and reporting the data obtained in scientific researches, being able to have researcher qualification with occupational sense of responsibility, having the scientific and vocational ethics’ understanding and being able to defend this understanding in every medium. TEXTBOOK (Turkish) Karasar, N. (2015). Bilimsel Araştırma Yöntemi. Nobel Akademi Yayıncılık, Ankara. OTHER REFERENCES 1-Büyüköztürk, Ş., Çakmak, E. K., Akgün, Ö. E., Karadeniz, Ş., Demirel, F. (2012). Bilimsel Araştırma Yöntemleri. Pegem Akademi Yayınevi, Ankara. 2-Tanrıöğen, A. (Editör). (2014). Bilimsel Araştırma Yöntemleri. Anı Yayıncılık, Ankara.
DEPARTMENT INDUSTRIAL ENGINEERING (MSc) SEMESTER COURSE CODE TITLE Human Machine Interaction LEVEL HOUR/WEEK Credit ECTS TYPE LANGUAGE Theory Practice Laboratory MSc 3 0 0 3 7,5 COMPULSORY ( ) ELECTIVE ( x ) Turkish CREDIT DISTRIBUTION Science Engineering Knowledge in the discipline [if it contains considerable design content, mark with ()] 1 2 ASSESSMENT CRITERIA SEMESTER ACTIVITIES Evaluation Type Number Contribution ( % ) Midterm 2 40 Quiz Homework Project 1 25 Report Seminar ) Final Examination 35 PREREQUISITE(S) SHORT COURSE CONTENT Introducing the widely used interface design and usability methods with the support of sample cases. COURSE OBJECTIVES Making the students gain abilities to problems related with human machine design, analyze them, gather relevant data and find solutions out. COURSE CONTRIBUTION TO THE PROFESSIONAL EDUCATION The course aims to teach relevant methods for generating projects and solving problems in such various areas as manufacturing, service industry and academy. LEARNING OUTCOMES OF THE COURSE Comrehendson, Implementation, Analysis, Evaluation TEXTBOOK Dix. A, Finlay J., Abowd G.D., Beale R., 2004, Human Computer Interaction, Pearson Education Ltd. REFERENCES Shneiderman B., C. Plaisant, et al., 2017, Designing the User Interface, Addison Wesley.