GRADUATE COURSE DETAILS - fbe.balikesir.edu.trfbe.balikesir.edu.tr/fbe/docs/dersicerikleri/en/endmuh_en.pdf · Taha H.A., Yöneylem Araştırması, Literatür Yayıncılık, 2000

GRADUATE COURSE DETAILS

Course Title: Linear Optimization

Code : ENM

5101

Institute: Science and Technology

Field: Industrial Engineering

Education and Teaching Methods Credits Lecture Application Lab. Project/

Field Study Homework Other Total Credit

T+A+L=Credit ECTS

42 0 0 0 56 84 182 3+0+0=3 6

Semester Autumn/Spring Language Turkish/English

Course Type

Basic Scientific

Scientific Technical Elective

Social Elective

Course Objectives

Teaching of linear models and programming, and understandings of solution methods.

Learning Outcomes and Competencies

1. To be able to define the concept of optimization, classify and establish relationships with the other disciplines.

2. To recognize linear problems.

3. To be able to model linear problems. 4. To be able to apply the simplex method to model the problem. 5. To use other types of simplex methods and the two-phase method.

6. To establish the model of goal programming problems. 7. To use linear programming approach to Data Envelopment Analysis. 8. To use LINDO optimization software program in the solution of the problems.

Textbooks and /or References

1. Taha H.A., “Operations Research”, Prentice Hall, (2000). 2. Winston W.L., “Operations Research, Applications and Algorithms”, Duxbury Press, (1994). 3. Rardin R.L., “Optimization in Operations Research”, Prentice Hall, (1998).

ASSESSMENT CRITERIA

Theoretical Courses Project Course and Graduation Study

If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)

Midterm Exams Midterm Exams

Quizzes Midterm Controls

Homework Term Paper

Term Paper, Project Reports, etc.

Oral Examination

Laboratory Work Final Exam

Final Exam X 100 Other

Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Optimization fundamentals

Classical optimization theory Reviewing basic linear models Simplex method

Revised simplex method programming Big M method Two phase

Dual simplex method Diversification Goal programming (1) Goal programming (2)

Data envelopment analysis (1) Data envelopment analysis (2) General review

Instructor/s Prof. Dr. Ramazan Yaman

e-mail [email protected]

Website


Course Title: Project Management

Code : ENM 5102

Institute: Science and Technology Field: Industrial Engineering

Education and Teaching Methods Credits

Lecture Application Lab. Project/ Field Study

Homework Other Total Credit T+A+L=Credit

ECTS

96 0 0 0 50 50 196 3 6


Course Type

Basic Scientific Scientific

Technical Elective

Social Elective

Course Objectives

Project management principles, methodologies, tools and techniques to create a basic understanding about.


LO1 Define the basic concepts of project and project management. LO 2 Define project processes LO 3 Project planning techniques knows and capable of planning the project. LO 4 The project management process evaluates. LO 5 The project network creates, calculate the project completion times LO 6 The cost-time relationships of projects can analyze


1. Taha H.A., Yöneylem Araştırması, Literatür Yayıncılık, 2000. 2. Winston W. L., Operations Research Applications and Algorithms, International Thomson

Publishing, 2004. 3. Öztürk A., Yöneylem Araştırması, Ekin Kitabevi, 2004. 4. Albayrak B., Proje Yönetimi ve Analizi, Nobel Yayın Dağıtım, 2009

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Introduction to project management, Defining project management Project goals Classification of projects Project planning Organization charts in Project management Gantt chart CPM and PERT methods transition from Gantt chart Principles of drawing networks CPM and PERT methods Account the the completing time of Project, finding the critical path, account of the abundance, Time cost analysis Application with MS-Project package Application with MS-Project package

Instructor/s Asist. Prof. Dr. Demet GÖNEN


Website http://endustri.balikesir.edu.tr/index.php?sayfa=akademik_personel


Course Title: Advanced topics in quality control

Code : ENM 5103

Institute: Science Field: Industrial Engineering




ECTS

96 0 0 0 50 50 196 3 6


Course Type

Basic Scientific


Social Elective

Course Objectives

To give Total Quality Management Philosophy and to teach how to manage process control


LO1 Understand quality concepts, the dimensions and factors of quality LO2 Understand Total Quality Management and its principles and implement them on company LO3 Define departments and staffs responsibilities regarding quality in an organization LO4 Calculate quality cost LO5 Understand TS-EN-ISO 9000 :2008 Quality Management System, its scope and the way it is implemented LO6 Total Quality Management approach and techniques apply in business life .


1. Sadioğlu Sedat.,”Kalitenin Boyutları”,Gim Ofset,Ankara,2000. 2. Burnak Nimetullah.,”Toplam Kalite Yönetimi” Tekam Yayınları, Eskişehir, 1987. 3. Ersen Haldun.,"Topyekün Mükemmelleşme Sürecinde İnsan Kaynakları ve Kalite ” Maestro Yayın, İstanbul, 2002. 4. Ishikawa Kaoru.,”Toplam Kalite Kontrol”, Kalder Yayınları, İstanbul,1997. 5. Bozkurt Ridvan, Kalite İyileştirme Araç ve Yöntemleri, MPM, 2003. 6. Akkurt Mustafa, Kalite Kontrol Excel Destekli, Birsen Yayınevi, 2002 7. Bozkurt Ridvan, Kalite Maliyetleri, MPM, 2003

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Concept and definition of quality,historical development of quality, design of quality Quality gurus. Definition and principles of Total Quality Management Principles of TQM, Quality Costs Quality tools Quality control charts Process control methods Failure mode and effect analysis Quality Function Deployement (QFD) Taguchi Hoshin-Kanri Quality assurance systems EFQM excellence model and self-assessment





Course Title: Expert Systems

Code : ENM 5104






ECTS

42 0 0 0 56 84 182 3+0+0=3 6


Course Type


Technical Elective

Social Elective

Course Objectives

To gain the ability to develop expert systems.


1. To define the relationship between the concepts of Artificial Intelligence and Expert

Systems. 2. To define the elements of an expert system. 3. To identify the needed resources to select an appropriate problem to develop the system.

4. To be able to select development tools 5. To be able to test and evaluate the system. 6. Can use Prolog software program to develop an expert system.


1. Artificial Intelligence: A modern approach, S. Russell, P. Norvig, Prentice Hall Series in Artificial Intelligence, 2002. 2. Uzman Sistemler, Novruz Allahverdi, Nobel Akademik Yayıncılık, 2002.

3. Yapay Zeka. (İnsan – Bilgisayar Etkileşimi), Prof. Dr. Vasif Vagifoğlu Nabiyev, Seçkin Yayıncılık, 2010.

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Artificial Intelligence Technologies Introduction to Expert Systems Knowledge Acquisition

Knowledge Representation Design of expert systems Inference Methods

Backward Chaining, Forward Chaining Development of expert systems Expert System Software

Prolog with Expert Systems Prolog with Expert Systems Presentations General Reviews

Instructor/s Asist. Prof. Dr. Kadriye ERGÜN e-mail [email protected]

Website http://endustri.balikesir.edu.tr/~kergun


Course Title : Design of Experiments

Code : ENM 5105

Institute : Science and Technology Field : Industrial Engineering




ECTS

42 0 0 0 70 128 240 3 6


Course Type

Basic Scientific


Social Elective

Course Objectives

Learning the basic concepts and methods of experimental design.


LO 1 Having ability of designing experiments LO 2 Using response surface methodology

LO 3 Using Taguchi methodology LO 4 Using factorial design LO 5 Modeling Experimental results

LO 6 Performing optimization by using the models obtained from experimental results LO 7 Using design of experiments modules of statistical package programs


1. Design and Analysis of Experiments, Douglas C. Montgomery, John Wiley & Sons Inc., New York, USA, 2001.

2. Applied Statistics and Probability for Engineers, Douglas C. Montgomery, John Wiley & Sons Inc., New York, USA, 1999. 3. Kalite için Deney Tasarımı, Mete Şirvancı, Literatür Yayınları, İstanbul, 1997.

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Introduction to design of experiments Experiments with one factor Experiments with one factor Factorial experiments Factorial experiments Fractional experiments Fractional experiments Response surface methods and designs Response surface methods and designs Taguchi approach Taguchi approach Project representations Project representations General review

Instructor/s Asist. Prof. Dr. Aslan Deniz KARAOĞLAN




Course Title: Decision Support Systems

Code : ENM 5106





T+A+L=Credit ECTS

42 0 0 0 56 84 182 3+0+0=3 6


Course Type


Technical Elective

Social Elective

Course Objectives

It aims to teach analysis of decision making process and understanding of decision support systems


1. To interpret the challenges and the importance of decision -making.

2. To be able to define Decision Support Systems and its components. 3. To design a Decision Support System database. 4. To develop a new decision support system.

5. To use and utilize software programmes that are developed for Decision Support Systems.


1. Sauter, V.L., “Decision Support Systems”, Wiley, (1997).

2. Turban E., Aronson J. E., “Decision Support Systems and Intelligent Systems”, Prentice-Hall, (2001).

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Fundamentals of decision making Decision making process Difficulties of decision making Qualitative approaches for decision making Quantitative approaches for decision making Scenarios for decision making (1) Scenarios for decision making (2) AI and ES for decision making Uncertainties and inconsistencies Information presentation by formulized symbolic logic Subjects and techniques of information management Decision making tools (1) Decision making tools (2) General Overview



Website


Course Title: Methods of Process Improvement

Code : ENM 5107




T+A+L=Credit ECTS

96 0 0 0 50 50 196 3 6


Course Type


Technical Elective

Social Elective

Course Objectives

Analyzing and solving problems encountered in the environment.


LO1 Determine process components LO2 Realize documentation of processes LO3 Determine the adequacy of the production process LO4 Implement methods of process improvement


1. Bozkurt R., Kalite İyileştirme Araç ve Yöntemleri, MPM, 1998 2. Akkurt M., Kalite Kontrol Excel Destekli, Birsen Yayınevi, 2002 3. Bozkurt R., Süreç İyileştirme, MPM, 2002

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


X 30 Oral Examination


Final Exam x 70 Other

Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

The concept of process Process Documentation Process Capability Analysis Process Capability Analysis Methods of Process Capability Analysis Methods of Process Capability Analysis Case Studies Process Improvement Methods Used in Process Improvement Studies Brainstorming Pareto Analysis Cause Effect Diagram Scatter Diagram Presentation





Course Title: Flexibility in Production and Lean Production System

Code : ENM 5108



Field Study Homework

Other Total Credit T+A+L=Credit

ECTS

42 - - 42 - 156 240 3 6

Semester

Autumn

Language

Turkish

Course Type Basic Scientific

Scientific Technical

Elective Social Elective

Course Objectives

To teach students the places and the importance of new technologies, flexibility and lean process in production.


1- Learns the origins of modern production. 2- Learns Post-Fordist production relations.

3- Learns the principles and characteristics of flexible manufacturig. Implements them.

4- Reviews the impact of advanced manufacturing technologies in the labor force. 5- Learns group technology and Cellular Manufacturing 6- Interprets the use of robots in production.

7- Learns the lean manufacturing and management. Create value stream maps. Lean

manufacturing system sets up. 8- Learns the quick response manufacturing. Sets up quick, responsive production system. 9- Learns the 6 Sigma method and implements this method.


1- Tekin Akgeyik; "Strategic Production Management", Sistem Pub. İstanbul, 1998. 2- James P. Womack, Daniel T. Jones,Daniel Roos; "The Machine That Changed the World : The

Story of Lean Production" MIT Pub., USA, 1991. 3- Daniel T. Jones, James P. Womack; “The Lean Thinking”, Trans.: Nesime Aras, Sistem Pub., Nr:

163, Istanbul, 2002. 4- Mikel P. Groover; "Automation, Production Systems, and Computer-Integrated Manufacturing",

Prentice Hall Pub., Third Ed., USA 2007.

ASSESSMENT CRITERIA Theoretical Courses Project Course and Graduation Study

If any, mark as (X)

Percent (%)

If any,

mark as (X)

Percent (%)



Homework Term Paper


50

Oral Examination


Final Exam 50 Other

Other

Week Subjects

1 2 3

4 5 6 7

8 9 10 11

12 13 14

The Concept of Modern Manufacturing and The Origins of Modern Production. Handcrafts productions, Mass Productions and Taylorism Conveyor System and Fordism Supermarket Systems and Just in Time Toyotaism Crisis of Fordism and Post Fordism Lean Thinking, Manufacturing and Management Flexible Manufacturing Structures Flexible Production Elements and Technologies Group Technology and Cellular Manufacturing Automated Material Handling Systems Robots in the production process Quick Response Manufacturing 6 Sigma Applications

Instructor/s Asst.Prof.Dr.Özay Umut TÜRKAN


Website -

mailto:[email protected]


Course Title : Artificial Neural Networks

Code : ENM 5109




T+A+L=Credit ECTS

42 0 0 0 70 128 240 3 6


Course Type


Technical Elective

Social Elective

Course Objectives

To inform students about different artificial neural network algorithms and their applications to engineering problems.


LO 1 Understanding the working principles of artificial neural networks (ANN) LO 2 Using Multy Layer Perceptron (MLP) networks for solving the engineering problems LO 3 Using Linear Vector Quantization (LVQ) networks for solving the engineering problems LO 4 Using Elman networks for solving the engineering problems LO 5 Performing ANN algorithms by using softwares


1. Yapay Sinir Ağları, Ercan Öztemel, Papatya Yayıncılık , İstanbul, 2003. 2. Yapay Sinir Ağları, Çetin Elmas, Seçkin Yayıncılık , Ankara, 2003. 3. Mühendislikte Yapay Zeka Uygulamaları-I: Yapay Sinir Ağları, Şeref Sağıroğlu, Erkan Beşdok ve

Mehmet Erler, Ufuk Yayıncılık , Kayseri, 2003. 4. Yapay Sinir Ağları, Zekai Şen, Su Vakfı Yayınları, İstanbul, 2004.

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Artificial intelligence and overview of machine learning Introduction to artificial neural networks Structure of artificial neural networks and its fundamental elements Previous artificial neural networks Multy layer perceptrons (Supervised learning) LVQ networks (Reinforcement learning) ART networks (Unsupervised learning) Elman networks (Recurrent neural networks) Combined neural networks Artificial neural network applications with MATLAB Artificial neural network applications with MATLAB Artificial neural network applications with MATLAB Industrial applications of artificial neural networks General review

Instructor/s Asist. Prof. Dr. Aslan Deniz KARAOĞLAN




Course Title: Economy of Turkey

Code : ENM 5112

Institute: Science of Institue Field: Industrial Engineering



T+A+L=Credit ECTS

42 - - 50 100 48 240 3+0+0=3 6

Semester Autumn Language Turkish

Course Type


Technical Elective

Social Elective

Course Objectives

It is aimed to study Turkish Economy with its historical and structural elements. The format ion of

economic policies and internal and external factors that effect these formations, institutional

regulations, related data will be covered in a casual perspective as a whole.

Learning Outcomes and Competences

Learn the historical progresses . Understand the historical progresses by different time periods in

Turkish Economy s by different time periods in Turkish Economy. Analyze the Turkish economical

data. Asses the economical politics applied in Turkey. Compare Turkish economy with others .

Textbook and /or References

ŞAHİN, H. , 2007, Türkiye Ekonomisi, Ezgi Kitabevi, Bursa, 620s. EĞILMEZ, M., KUMCU, E., 2004, Ekonomi Politikası, Remzi Kitabevi, İstanbul

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework X 40 Term Paper





Other X 10

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Economic Structure in the Ottoman Period

Economic Structure in the First Ten Years of Republic

Industrialism Period

Economic Developments in the Second World War Period

Turkish Economy in the Planned Period

January 24th Decisions - April 5th Decisions

Turkish Economy in the Import Substitution and Export Promotion Periods

Agriculture Sector in Turkey

Industrialization Sector in Turkey

Sevice Sector in Turkey

Banking Sector in Turkey

Foreign Economic Relationships

Current Economic Topics Related to Turkish Economy

Instructor/s Asst.Prof.Dr.Şimal Yakut Aymankuy


Website

GRADUATE COURSE DETAILS Course Title: Role of Human Resources in

Total Quality Management

Code : ENM 5115 Institute: Science and Technology Field: Industrial Engineering



T+A+L=Credit ECTS

42 - - 42 - 156 240 3 8

Semester

Autumn

Language

Turkish

Course Type Basic

Scientific


Elective Social Elective

Course Objectives

To evaluate the changing role and efficiency of human factor in Total Quality Management, and introduce the necessity and importance of the integration of labor force and production organizations.


1- Learns the origins of Total Quality Management

2- Learns the principles and characteristics of Total Quality Management. Implements them. 3- Learns to create a flexible production and working process. 4- Reviews the impact of advanced manufacturing technologies in the labor force. 5- Learns participatory management and small group activities. 6- Creates labor plan according to the demand. 7- Plans in service and out of service training that the workforce needs. 8- Measures and evaluates the performance of the labor force.


1- Jeffrey Pfeffer; “Competitive Advantage Through People: Unleashing the Power of the Work Force”, Trans: Sinem Gul, Sabah Pub., Istanbul, 1995. 2- Robert H. Rosen; “People Management”, Trans.: Gündüz Bulut, Mess Pub., Nr: 260, Istanbul, 1998. 3- Tekin Akgeyik; “Strategic Production Management”, Sistem Pub., Istanbul, 1998. 4- Yoshio Kondo; “Total Quality in Enterprise”, Trans.: Ayşe Bilge Dicleli, Mess Pub., Nr: 300, Istanbul, 1999.

ASSESSMENT CRITERIA


If any, mark as (X)

Percent (%)

If any, mark as (X)

Percent (%)



Homework Term Paper


50

Oral Examination


Final Exam 50 Other

Other

Week Subjects 1 2 3 4 5

6 7 8 9

10 11

12 13

14

The origin of the Total Quality Management and Management Approaches Change Management and Organizational Transformation TQM as a Concept – Principles of TQM Applications for Perfection, Consumer Centered Policies, Competition Lean and Flexible Production

Effects of Advanced Technology on Production Process Transformation in Business Life: Flexible Work A New Concept : “ Employee” - Definition of Human Factor and Responsibility Participatory Management Approach

Team Work: Kaizen, Quality Circles, Project Groups… Job Analysis, Job Evaluation, Payment Planning Human Resources Training and Development

Performance Evaluation



Website -



Course Title: Database Management Systems

Code : ENM 5123






ECTS

42 0 0 0 56 84 182 3+0+0=3 6


Course Type


Technical Elective

Social Elective

Course Objectives

To understand, use, and construct a data base.


1. To recognize database management systems. 2. To establish a relation with the particle and associational data models . 3. To create database, tables and queries by SQL. 4. Can use software programmes that use database systems.


1. Ramakrishnan R., Gehrke J., “Database Management Systems”, UC Berkeley Engineering, (2006).

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Introduction to data base concept and design Relational data models SQL and data dictionary Database management Database system architecture Usage and development of data base and distributed data base systems and their development environments (2 weeks) Commercial data base systems (1) Commercial data base systems (2) Development of a database prototype in a project team(1) Development of a database prototype in a project team (2) Development of a database prototype in a project team (3) Development of a database prototype in a project team (4) Presentation (1) Presentation (2)



Website


Course Title: Entrepreneurship

Code : ENM 5124





T+A+L=Credit ECTS

42 0 0 0 70 92 204 3 6

Semester 2 Language Turkish

Course Type

Basic Scientific

X Scientific Technical Elective

Social Elective

Course Objectives

Students can learn basic terms related with entrepreneurship Students can learn exercises with entrepreneurship Students can learn the problems of entrepreneurship in Turkey Students can learn the the opportunities of entrepreneurship in Turkey Students can learn the policy of entrepreneurship in Turkey Students can learn international entrepreneurship major differences

Objectives of the Course

It will create a theoretical foundation on the national and international entrepreneurship


Essentials of Entrepreneurship and Small Business Management S.Edt. Thomas Zimmerer, Norman Scarborough,Dough Wilson, March 2007, Pearson

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)





Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Fundamental Principles for Entrepreneurship Fundamental Principles for Entrepreneurship Entrepreneurship Problems in Turkey Entrepreneurship Problems in Turkey Opportunities and Policy Entrepreneurship in Turkey Opportunities and Policy Entrepreneurship in Turkey International Entrepreneurship Major Differences International Entrepreneurship Major Differences Case Studies Case Studies Case Studies Case Studies Case Studies Case Studies

Instructor/s Yrd.Doç.Dr.Burhan Aydemir



Course Title: Applied Mathematics for Engineers

Code : ENM 5125




T+A+L=Credit ECTS

28 14 0 0 0 48 90 3+0=3 6

Semester 2 Language Turkish

Course Type

Basic Scientific


Social Elective

Course Objectives

Teaching of numerical methods when mathematical models of physical systems can not be solved analytically or analytical solutions are hard to solve or take long time for engineering problems.


Selection ability of a suitable numerical method for a mathematical problem, application, finding a better solution approach in an economical manner.


Gerald, C., F., Wheatley, P., O., “Applied Numerical Analysis”, Addison Wesley Pub., 1984. Karagöz, İ., “Sayısal Analiz ve Mühendislik Uygulamaları”, Nobel Yayın No:1281, 2008 Çağal, B., “Sayısal Analiz”, Seç Yayıncılık, 1989

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)

Midterm Exams X 40 Midterm Exams


Homework Term Paper


Oral Examination



Other X -

Week Subjects

1 2 3 4 5 6 7 8 9 10 11

12 13 14

-Numbers, Errors and Computer Accuracy -Floating-Point Form of Numbers, Programming Errors, Errors of Numerical Results, -Numerical Solutions of Non-Linear Equations, Fixed-Point Iteration Method, Newton-Raphson Method, Bisection and Regula-Falsi Method -Taylor Series Expansions -Finite Differences and their Tables -Numerical Differentiation - Gregory-Newton Interpolation Methods -Numerical Integration, The Trapezium and Simphson Rules -Interpolation Linear and Quadratic Interpolation, Gregory-Newton Interpolations -Numerical Methods in Linear Algebra Gauss’s Elimination Methods, LU Factorisation, Gauss -Seidel Iteration Method Ordinary Initial-Value Problems, Taylor Series Method, Euler’s Method, Runge-Kutta Methods -Curve Fitting (Method of Least Squares) - Finding diferrent fonksions with Least Squares Methods

Instructors Assistant Prof. Dr. Gülşen Yaman


Website


Course Title: Advanced Facility Layout Code : ENM 5202




T+A+L=Credit ECTS

42 0 0 0 56 84 182 3+0+0=3 6


Course Type


Technical Elective

Social Elective

Course Objectives

It investigates algorithms that could be used facility layout problem solutions


1. To classify, and set the facility layout of any service and production systems 2. To draw facility layout diagrams based on the flow of the product or service. 3.To apply the assembly line balancing methods . 4. To design different facility layouts according to flow of production or service . 5. To be able to use computer-aided facility design programs, and apply algorithms. 6. Evaluate and decide the developed/improved facility layout designs.


1. Sule D.R., “Manufacturing Facilities: Location, Planning, and Design”, PWS-Kent Publishing Co., (1988).

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Introduction to rank problems Single machine problem Workshop and work flow Optimal processes Dynamic programming approach Integer programming Branch and bound method Complexity of rank problems Heuristic algorithms (1) Heuristic algorithms(2) Artificial intelligence applications on rank problems Case problems (1) Case problems (2) General overview



Website


Course Title: Manufacturing Resources Planning

Code : ENM 5203






ECTS

42 0 0 0 56 84 182 3+0+0=3 6


Course Type


Technical Elective

Social Elective

Course Objectives

To teach production planning basics and implementation


1. To identify and classify the basic characteristics of production systems.

2. To be able to create product tree and generate coding system. 3. To define the differences and relations between Material Requirements Planning and Manufacturing Resource Planning.

4. To design the necessary modules in Manufacturing Resource Planning systems based on the type of production. 5. Can do capacity requirements planning.

6. To gain a basic knowledge of Customer Relationship Management, Product Lifecycle Management, Distribution Resource Planning.


1. Sipper D., Bulfin R.L., “Production: Planning, Control, and Integration”, McGraw -Hill, (1997).

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Production planning Fundamentals Importance of codes for production planning Bill of Materials and its requirements Material Requirements Planning (MRP) (1) Material Requirements Planning (MRP) (2) Manufacturing Recourses Planning (MRP II) (1) Manufacturing Recourses Planning (MRP II) (2) Enterprise Resources Planning (ERP II) (1) Enterprise Resources Planning (ERP II) (2) Enterprise Resources Planning (ERP II) (3) Short, Medium, Long Term Planning Capacity planning Packages for production planning (SAP, CANIAS, BAAN) Packages for production planning (SAP, CANIAS, BAAN)


e-mail [email protected] Website


Course Title: Nonlinear Optimization

Code : ENM 5205





T+A+L=Credit ECTS

42 0 0 0 56 84 182 3+0+0=3 6


Course Type


Technical Elective

Social Elective

Course Objectives

To teach nonlinear optimization and its solution algorithms.


1. To define the non-linear optimization problems. 2. To model non-linear optimization problems. 3. To be able to apply different techniques for the solution of non-linear optimization. 4. To decide which method in the solution of the problem


1. Nash S.G., Sofer A., “Linear and Nonlinear Programming”, McGraw-Hill, (1996) 2. Luenberger D.G., “Introduction to Linear and Nonlinear Programming”, Addison,Wesley Publishing, (1973). 3. Winston W.L., “Operations Research, Applications and Algorithms”, Duxbury Press , (1994). 4. Rardin R.L., “Optimization in Operations Research”, Prentice Hall, (1998).

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

General principles of algorithm formations Cauchy and Newton strategies One dimensional search

Linear least squares Nonlinear least squares Gauss-Newton and Marquardt algorithms

Quasy-Newton type methods Quadratic programming Convex programming

Slater condition Duality, projection of R

n solution space

Mirror gradient algorithm

Sequential quadratic programming Other solution approaches


e-mail [email protected] Website


Course Title: PERFORMANCE MEASUREMENT IN BUSINESSES

Code : ENM 5206

Institute: Science of Institue Field: Industrial Engineering




ECTS

42 - - 50 100 48 240 3+0+0=3 6

Semester Spring Language Turkish

Course Type

Basic Scientific


Social Elective

Course Objectives

The course aims to provide the students with a general knowledge on Performance in Business, Dimensions, Produce


List prepare stages of investment project. Explain prepare stages of investment project. Use investment project evaluation methods.

Compare investment project evaluation methods. Arrange investments of the business according to results to get from investment project evaluation methods.


Emir, M. 2008, Yat ırım Projelerinin Hazırlanması ve Değerlendirilmesi, Derya Kitabevi, Trabzon. CLACK, John, J. And HINDELONG, T. J. Capital Budgeting and Control of Capital

Expenditures, Third Edition Prentice-Hall International. SARIASLAN, H.(2004), Yatırım Projelerinin Hazırlanması ve Değerlendirilmesi, Alfa Yayınları, İstanbul.

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)








Other X 10

Week Subjects

1 2 3 4 5 6

Basic concepts related to investment projects. Investment types, the basic stages of investment projects. Preparation of investment projects: the emergence of the idea of the project area and

the most appropriate investment selection. The preparation of investment projects, feasibility analysis. Economic analysis of investment projects: Market research, demand estimation and

forecasting methods. Site selection organization for investment projects. Organizations that affect the site selection factors. Site selection and location of the region. Establishment site selection

methods. Site selection organization for investment projects. Organizations that affect the site selection factors. Site selection and location of the region. Establishment site selection

methods. Technical analysis of investment projects. General description and technical evaluation issues.

7 8 9

10

11 12

13

14

Financial analysis of investment projects. Determination of cash flows o f investment projects. Determination of period cash flow organization. The determination of the winter operation period cash.

Evaluation of investment projects. Not take into consideration the time value of money ways: A simple method of profit rate, the average profit rate and repayment period method. Methods of evaluation.

Internal profitability (efficiency) ratio method, internal rate of profitability with net present value method for the evaluation method. Adjusted internal profitability rate method.

Economic evaluation of life with different yaırım project. Common approach to li fe, and eternal life-year approach equal anuiye approach. Evaluation of investment projects in the inflationary environment. Effect of inflation on investment projects.

Evaluation of investment projects in the inflationary environment. Risky investment projects evaluation methods to determine the overall risk concepts. Sensitivity analysis to measure the risk. Break-even point analysis, the safety margin,

operating leverage, financial leverage and total leverage. Sensitivity analysis to measure risk: Reduced cash flows method. Probability analysis to measure risk: Risk adjusted discount rate method, specificity equality approach.

Expected net present value method, the expected net cash flows method and decision tree method.

Instructor/s Asist. Prof. Dr. Şimal Yakut AYMANKUY


Website -


Course Title: Fuzzy Logic and Engineering Application

Code : ENM 5207




T+A+L=Credit ECTS

96 0 0 0 50 50 196 3 6


Course Type

Basic Scientific


Social Elective

Course Objectives

to learn Fuzzy logic set theory, to learn the basic structure of fuzzy logic controller, to design fuzzy logic controllers.


LO1 Understands basic knowledge about fuzzy logic LO 2 Enabling Design of Fuzzy Control Rules LO 3 Comprehends fuzzy inference methods. LO 4 Understands using the fuzzy logic for encountered problem


1. Elmas, C., (2007) Yapay Zeka Uygulamaları, Seçkin Yayınevi. 2. Nabiyev V. V., (2005), Yapay Zeka Problemler - Yöntemler - Algoritmalar, Seçkin Yayıncılık 3. Baykal, N. – Beyan, T., (2004), Bulanık Mantık İlke ve Temelleri , Bıçaklar Kitabevi

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

The concept of fuzziness, Introduction to fuzzy logic fuzzy set theory, Properties of fuzzy sets Fuzzy logic principles. Basic fuzzy operations: Union, intersection, complement, etc. The basic structure of fuzzy logic controller System variables and fuzzy parameters Fuzzification strategies, Creating knowledge base Fuzzy inference techniques Clear strategy and design of fuzzy control rules Fuzzy logic controller related to design and practices Obtaining a mathematical model of dynamic system Matlab fuzzy applications. Matlab fuzzy applications.




http://www.seckin.com.tr/search.aspx?key=Vasif%20V.%20Nabiyev

http://www.seckin.com.tr/search.aspx?key=Se%E7kin%20Yay%FDnc%FDl%FDk

http://www.seckin.com.tr/urun.aspx?productID=154

http://www.seckin.com.tr/search.aspx?key=B%FD%E7aklar%20Kitabevi


Course Title: Preparing A Business Plan

Code : ENM 5208




T+A+L=Credit ECTS

42 0 0 0 70 128 240 3 6

Semester Autumn/Spring Language Turkish

Course Type


Technical Elective

Social Elective

Course Objectives

In a matter of preparing a business plan


To learn how to prepare a business plan.


www.kosgeb.org.tr

www.girisimcilik.org

www.girisimcilik.gen.tr

Atış C. , Ertekin G. Y. , Yurtsever Ş., Girişimcilik”, Karahan Yayınları, 2006

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


x 30 Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Investigating the properties of subjects and instituons that is suggested for business plan Analyzing of the business plans previously successful or unsuccessful Preparing draft business plan Purveyance of data and sources that necessary for the business plan, adapting to topic Elaboration of the business plan Elaboration of the business plan Checking about contents and format Work plans for sample business plan Preparing sample business plan Preparing sample business plan Preparing sample business plan Preparing sample business plan Preparing sample business plan Presentations

Instructor/s Asst.Prof.Dr. Burhan AYDEMİR


Website

http://www.kosgeb.org.tr/

http://www.girisimcilik.org/

http://www.girisimcilik.gen.tr/

http://kitap.antoloji.com/kisi.asp?CAS=206071




Course Title : Artificial Intelligence Optimization Algorithms

Code : ENM 5209




T+A+L=Credit ECTS

42 0 0 0 70 128 240 3 6


Course Type Basic Scientific Scientific

Technical Elective

Social Elective

Course Objectives

To gain the ability to use the meta-heuristic methods for solving optimization problems.


1. Understanding the artificial intelligence techniques. 2. Having ability of modeling, solving, and evaluating the engineering problems by using artificial neural networks 3. Having ability of modeling, solving, and evaluating the engineering problems by using tabu search algorithm 4. Having ability of modeling, solving, and evaluating the engineering problems by using genetic algorithms 5. Having ability of modeling, solving, and evaluating the engineering problems by using ant colony algorithm 6. Having ability of modeling, solving, and evaluating the engineering problems by using simulated annealing


1. Yapay Zeka (İnsan –Bilgisayar Etkileşimi), Prof.Dr. Vasif Vagifoğlu Nabiyev, Seçkin Yayıncılık, 2010. 2. Yapay Zeka Optimizasyon Algoritmaları, Derviş Karaboğa, Atlas Yayın Dağıtım , 2004.

3. Artificial Intelligence: A modern approach, S. Russell, P. Norvig, Prentice Hall Series in Artificial Intelligence, 2002. 4. Yapay Sinir Ağları, Ercan Öztemel, Papatya Yayıncılık, 2003.

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)

Midterm Exams Midterm Exams Quizzes Midterm Controls Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Definition of Artificial Intelligence and AI Technologies. Optimization Classifying of Optimization Problems Classifying of Optimization Methods Heuristic Algorithms Artificial Neural Networks Artificial Neural Networks Genetic Algorithms Genetic Algorithms Tabu Search (1) Tabu Search (2) Simulated Anneling Ant Colony Algorithm Presentation

Instructor/s Asist. Prof. Dr. Kadriye ERGÜN




Course Title : Statistics and Its Software Applications

Code : ENM 5210





ECTS

42 0 0 0 70 128 240 3 6


Course Type


Technical Elective

Social Elective

Course Objectives

To inform students about basic concepts of statistics and its software applica tions.


LO 1 Students are able to compute, analyze and interpret descriptive by using statistical software LO 2 Students are able to draw appropriate graphs of data sets and analyze variability, distribution and relations of data sets by using statistical software LO 3 Students are able to compute probability and cumulative probability by using statistical software LO 4 Students are able to test and interpret normality of data by using statistical software LO 5 Students are able to compute confidence interval and interpret it by using statistical software LO 6 Students are able to test hypothesis and interpret the results by using statistical software LO 7 Students are able to make single and multi factor variance analysis by using statistical software


1. Cintas, P.D., Almogro, L.M., and Llabr'es, X.T.M., Industrial Statistics with Minitab, Wiley&Sons, (2012). 2. Rea, L.M. and Parker, R.A., Designing and Conducting Survey Research, Jossey-Bass, 4.ed, 2014.

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Introduction to Statistics Descriptive Statistics Descriptive Statistics Graphical Analysis Graphical Analysis Sampling Distributions Sampling Distributions Confidence Intervals Hypothesis Tests (One Sample) Hypothesis Tests (One Sample) Hypothesis Tests (Two Samples) Analysis of Variance (One Factor) Analysis of Variance (One Factor) Analysis of Variance (Two Factor)

Instructor/s Asist. Prof. Dr. Mustafa Ahmet Beyazıt OCAKTAN


Website


Course Title: Group Technology and

Flexible Manufacturing Systems

Lecture

42

Application

0

Semester

Course Type

Course Objectives Learning Outcomes and

Competencies


Basic Scientific

Code : ENM-5211 Institute: FBE

Field: Industrial Eng.

Total

204

Credits Credit ECTS T+A+L=Credit 3+0+0 8

Turkish

Social Elective

Education and Teaching Methods Lab. Project/ Homework

Field Study 0 0 70

Spring

Scientific

Language

Technical Elective

Other

92

To understand group technology and flexible manufacturing system fundamentals

One knows how to use advantages of group technology and flexible manufacturing systems

Nalbant Muammer, ‘Bilgisayarla Bütünleşik Tasarım ve İmalat’, Beta Yay ınlar ı, İstanbul 1997. Hasis, Siegmar, ‘CIM-Einführung in die rechnerintegrierte Produktion’ Carl Hanser Verlag, M ünchen 1992.

Groover, Mikel P., ‘Automation Production Systems and Computer Integrated Manufacturing’, Prentice Hall

Inc., New Jersey, 1987.

ASSESSMENT CRITERIA

Theoretical Courses

If any, mark as (X)

Percent (%)

40 Midterm Exams

Midterm Controls

x - Term Paper

Oral Examination

Final Exam

x

x

60

-

Other

Project Course and Graduation Study

If any, mark as (X)

Percent (%)

Midterm Exams

Quizzes

Homework


Laboratory Work

Final Exam

Other

Week

1 2 3

4 5 6 7 8

9 10 11 12 13

14

Instructor/s

e-mail

Website

x

Subjects

Introduction

Computer Aided Manufacturing (CAM)

CNC Machine

Machining Center

Flexible Manufacturing Cells Flexible Manufacturing Cells

Flexible Manufacturing Systems

Flexible Manufacturing Line

Flexible Manufacturing Components and Technology Flexible Manufacturing Components

Direct Numerical Control (DNC)

Group Technology

Effects of group technology to productivity

Automatic Vehicle Transport Systems (AVUS)

Assoc. Prof. Dr. Ziya AKSOY

[email protected]

http://w3.balikesir.edu.tr/~zaksoy


Course Title: Contemporary Concepts and Applications in Management

Code: ENM 5212 Institute: Science and Technology




T+A+L=Credit ECTS

42 0 0 42 0 156 240 3 6


Course Type

Basic Scientific


Social

Elective

Course Objectives

To evaluate the contemporary management philosophy enabling organizations to maintain their existence and develop themselves in the global competition, and diverse management approaches related to this philosophy.


1- Learns and implements management theories. 2- Learns and comments the reasons for the restructuring of enterprises. 3- Learns lean philosophy and builds lean management system. 4- Learns and applies solutions of the work monotony problem in production. 5- Strengthens the workforce and work organization. 6- Learns self-managed teams and makes group work. 7- Makes decisions such as downsizing, establishing strategic partnerships, outsourcing . 8- Learns importance of the supply relationships about flexible production and manages

the supply relationships. 9- Learns the standardization of quality and takes part in guality management processes.


1- Daniel T. Jones- James P. Womack; “Lean Thinking”, Trans..: Nesime Aras, Sistem Pub., Nr: 163,

Istanbul, 2002. 2- Ozcan Yeniceri; “Change in Organizational Management”, Nobel Pub., Nr:337, Ankara, 2002. 3- Thomas Gordon; “Participant Management Fundamentals”, Trans.: Emel Aksay, Sistem Pub., Nr: 136,

Istanbul, 1997. 4- Mustafa Yasar Tinar; “ Industrial Psychology”, Necdet Bukey Pub., 1. Ed., Izmir, 1996.

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper

Term Paper, Project Reports, etc. 50 Oral Examination


Final Exam 50 Other

Other

Week Subjects

1 2

3 4 5

6 7 8

9 10 11 12

13 14

Evolution of Management Idea Restructuring of Organizations and Reengineering

Lean Organization, Lean Production, Lean Management Job Enrichment, Job Expansion, Job Rotation Employee Empowerment

Team Managing Themselves Downsizing

Outsourcing Learning Organizations Benchmarking Virtual Organizations

Strategic Corporation/Merging Supply Chain Management

Quality Management Systems

Instructor/s Asst.Prof.Dr. Özay Umut TÜRKAN


Website -



Course Title: Image Processing Fundamentals

Code : ENM5213

Institute: Institute of Science and Technology Field: Industrial Engineering




ECTS

42 0 0 0 70 128 240 3 6


Course Type


Technical Elective

Social Elective

Course Objectives

Introduction to image processing techniques


1) To learn the fundamentals of image processing 2) To have the ability to image enhancements in spatial domain 3) To have the ability to image enhancements in frequency domain 4) To learn how to do image restoration 5) To learn how to do image compression


Digital Image Processing ISBN-10: 0130946508

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)

Midterm Exams x 30 Midterm Exams


Homework Term Paper


x 10 Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Intoduction. Characteristics of digital imaces. Image enhancements in spatial domain. Image enhancements in spatial domain. Image enhancements in spatial domain. Image enhancements in frequency domain. Image enhancements in frequency domain. Image enhancements in frequency domain. Image restoration. Image restoration. Image restoration. Image compression Image compression Image compression

Instructor/s Davut Akdaş


Website http://eee.balikesir.edu.tr/


Course Title: Quality Management Systems

Code : ENM 5215 Institute: Science and Technology Field: Industrial Engineering



T+A+L=Credit ECTS

42 - - 42 - 156 240 3 6

Semester

Spring

Language

Turkish

Course Type Basic

Scientific


Elective Social

Elective

Course Objectives

To teach the concept of quality management, to put forth the importance of quality standardization for businesses to teach criteria to ensure the sustainability of the-system and related techniques.


1- Learns quality concept, history of its, and the approach of the pioneers of quality, reviews 2- Learns quality processes. 3- Reviews Fordist production period with all the features and principles. 4- Defines flexible production & management processes and fictions system as a basis. 5- Learns the quality standards on procedural basis.and applies 6- Learns quality standardization and ensures the continuity of the system. 7- Learns quality marks using in international trade and designs appropriate product processes. 8- Learns, fictions and applies “Six Sigma”concept.


1- Turker Bas, Murat Oymak; “ISO 9001: 2000 Quality Management System ”, Seçkin Pub., 3. Ed., İstanbul, 2007. 2- Howard S Gitlow; “Quality Management Systems: A Practical Guide”, CRC Pres, USA, 2001. 3- Geoff Vorley, Fred Tickle; “Quality Management Principles & Practice”, Quality Management & Training (Publication), USA, 2002. 4- “Productivity and Quality Management: Modular Program”, Editors: Joseph PROKOPENKO, Klaus NORTH, VGM Pub., Nr: 716, Ankara, 2011. (http://vgm.sanayi.gov.tr/NewsDetails.aspx?newsID=2298&lng=tr) 5- Michael L. George, David Rowlands; “What is Lean Six Sigma”, McGraw-Hill Pub., USA, 2004.

ASSESSMENT CRITERIA


If any, mark as (X)

Percent (%)

If any, mark as (X)

Percent (%)



Homework Term Paper Term Paper, Project Reports, etc.

50

Oral Examination


Final Exam 50 Other

Other Week Subjects

1 2 3

4 5 6 7

8 9 10 11

12 13 14

The Concept of Quality and Quality History Important Quality Pioneers

Fordist Period: Quality Control Post Fordist Period: Competition and Total Quality Approach

Post Fordist Period: Flexible Production and Management Principles Standardization and Sustainability of Quality...

The Concept of Quality Management Systems: Principles, Characteristics. The Concept of Quality Management Systems: Costs, Benefits...

ISO 9001:2008 ISO 14001 ISO 16949 OHSAS 18001 CE Marking

Six Sigma and Quality Management



Website -

http://www.seckin.com.tr/browser/fa/514185746/title/dr-turker-bas.html

http://www.seckin.com.tr/browser/fa/346855421/title/murat-oymak.html

http://www.amazon.com/Howard-S-Gitlow/e/B001ILFN4I/ref=ntt_athr_dp_pel_1/185-8832797-2834414

http://www.google.com.tr/search?hl=tr&tbo=p&tbm=bks&q=inauthor:%22Geoff+Vorley%22&source=gbs_metadata_r&cad=4

http://www.google.com.tr/search?hl=tr&tbo=p&tbm=bks&q=inauthor:%22Fred+Tickle%22&source=gbs_metadata_r&cad=4

http://books.google.com.tr/url?id=blTDAQAACAAJ&q=http://www.qmt.co.uk/books/principlesnpractice.htm&linkid=2&usg=AFQjCNHRjnVBNVyFsMxh9ydOwu4ULTv9bg&source=gbs_web_references_r&cad=3

http://vgm.sanayi.gov.tr/NewsDetails.aspx?newsID=2298&lng=tr

http://www.amazon.com/s/ref=rdr_ext_aut?_encoding=UTF8&index=books&field-author=Michael%20L.%20George

http://www.amazon.com/s/ref=rdr_ext_aut?_encoding=UTF8&index=books&field-author=David%20Rowlands

http://www.amazon.com/dp/007142668X/ref=rdr_ext_tmb


POST GRADUATE COURSE DETAILS

Course Title: Numerical Solutions for Engineering Problems

Code : ENM 5216




Homework Other Total T+A+L=Credit ECTS

42 0 0 0 70 128 240 3+0+0=3 6

Semester Language Turkish

Course Type


Technical Elective

Social Elective

Course Objectives

Teaching of numerical methods when mathematical models of physical systems can not be solved analytically or analytical solutions are hard to solve or take long time for engineering problems.


LO1: to select a suitable numerical methods for a mathematical problems LO2: to apply numerical method on engineering problems LO3: to find the best solution for the nümerical problems and to make error analysis LO4: to solve lineer and non-lineer equations LO5: to use interpolatin methods LO6: to use methods of numerical differentiation and numerical integration LO7: to apply curve fitting methods to various data or experimental values


1. Sayısal Analiz ve Mühendislik Uygulamaları, İrfan Karagöz, Nobel Yayın, 2008. 2. Applied Numerical Analysis, C.F. Gerald, P.O. Wheatley, Addison Wesley Pub., 1984. 3. Mühendisler için Sayısal Yöntemler, S.C. Chapra, R.P. Canale, Literatür Yayınları,İstanbul, 2003 4. Sayısal Analiz, B. Çağal, Seç Yayıncılık, 1989.

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11

12 13 14

-Numbers, Errors and Computer Accuracy -Floating-Point Form of Numbers, Programming Errors, Errors of Numerical Results, -Numerical Solutions of Non-Linear Equations, Fixed-Point Iteration Method, Newton-Raphson Method, Bisection and Regula-Falsi Method -Taylor Series Expansions -Finite Differences and their Tables -Interpolation Gregory-Newton Interpolation Methods Linear and Quadratic Interpolation -Numerical Differentiation -Numerical Integration, The Trapezium and Simphson Rules -Numerical Methods in Linear Algebra Gauss’s Elimination Methods, LU Factorisation, Gauss -Seidel Iteration Method Ordinary Initial-Value Problems, Taylor Series Method, Euler’s Method, Runge-Kutta Methods -Curve Fitting (Method of Least Squares ) -Finding approximation fonksions with Least Squares Methods

Instructors Assistant Prof. Dr. Gülşen Yaman


Website


Course Title: Simulation Modeling and Analysis

Code : ENM 5217

Institute: Institute of Science Field: Industrial Engineering



T+A+L=Credit ECTS

3 0 0 3 3+0+0=3 6


Course Type


Technical Elective

Social Elective

Course Objectives

After this course, students will be able to model manufacturing/service systems with simulation, to form scenarios, to analyze and interpret simulation outputs.


1) Students will be able to determine simulation inputs and performance measurements by analyzing the manufacturing/service systems 2) Students will be able to analyze simulation inputs. 3) Students will be able to form the simulation models of manufacturing/service systems with ARENA 4) Students will be able to analyze finite and infinite horizon simulations and to interpret outputs. 5) Students will be able to compare simulation alternatives and make valid decisions based on statistical output of a simulation


1) Kelton, W.D., Sadowski, R.P. and Zupick, N.B., Simulation with Arena, McGraw-Hill Education, ISBN:978-1-259-25436-9 2) Rossetti, M.D., Simulation Modeling and Arena, John Wiley&Sons, ISBN:978-0-470-09726-7 3) Altıok, T. and Melamed, B., Simulation Modeling and Analysis with Arena, Academic Press, ISBN: 978

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)

Midterm Exams X %25 Midterm Exams


Homework X %15 Term Paper


Oral Examination


Final Exam X %60 Other

Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Introduction to simulation modeling Basic process modeling-I Basic process modeling -II Basic process modeling -III Input modeling-I Input modeling--II Advanced process modeling-I Advanced process modeling-II Finite horizon simulation Infinite horizon simulation Comparing alternatives Scenario analysis Modeling entity transfer and material handling constructs Simulation of queuing and inventory systems

Instructor/s Assist.Prof.Dr.M.A.Beyazıt OCAKTAN


Website w3.balikesir.edu.tr/~ocaktan


Course Title: Ergonomics and Computer-Aided Ergonomics Software

Code : ENM5218





ECTS

96 0 0 0 50 50 196 3 6


Course Type


Technical Elective

Social Elective

Course Objectives

To make ergonomic improvements in order to reduce work accidents and occupational diseases and to increase employee productivity.


LO 1 Understanding the primary goals of ergonomics, LO 2 Providing the congruence of work to human and human to work, LO 3 Correlating the ergonomics with human psychology, LO 4 Preventing the work accidents and occupational diseases, LO 5 Increasing the employee productivity by ergonomic regulations LO 6 Using the computer-aided ergonomics software.


Fatih C. Babalık, Ergonomics for Engineers, Nobel, 2008. Necmettin Erkan, Ergonomics, MPM, Publish No:373, 2000, 7th edition. MESS-REFA, Work System and Process Regulation Volume II, 2003. MPM-REFA, Work Study, Method Information, Volume-1, MPM, 1991. Bayram Ali Su, Ergonomics, Atılım Üniversity, 2000. M. Sanders, E. McCormick, Human factors in engineering and design, McGraw-Hill,1993.

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Human, human and performance, physical effort, static and dynamic work in terms of ergonomics,

Human and energy needs, mental actions, fatigue and resting Human-oriented work design Stress and monotony Rula and Reba Analysis Computer-aided ergonomics Computer-Aided Ergonomics Software Computer-Aided Ergonomics Software Computer-aided ergonomics software application (Anybody Modeling System-AMS) Computer-aided ergonomics software application (Anybody Modeling System-AMS) Computer-aided ergonomics software application (Anybody Modeling System-AMS) Motion capture system Motion capture system Evaluation of an assembly station with the motion capture system and AMS analysis.





Course Title : Text Mining Code : ENM5219

Institute :Science and Technology Field : Industrial Engineering


Lecture Application Lab. Project/

Field Study Homework Other Total

Credit T+A+L=Credit

ECTS

42 0 0 0 70 128 240 3 6


Course Type

Basic Scientific


Social Elective

Course Objectives

To gain the ability to develop information extraction system of textual data written in natural language.


1. To be able to define the basic concepts of data mining. 2. To be able to distinguish data, information, knowledge, wisdom concepts. 3. To be able to apply Information Retrieval methods.

4. To be able to apply Information Extraction methods.


1. Veri Madenciliği Yöntemleri, Yalçın Özkan, Papatya Yayıncılık, 2008. 2. Veri Madenciliği-Veri Analizi, Kolektif, 2014. 3. Temel Metin Madenciliği, Ayşe Oğuzlar, Dora Yayıncılık, 2011. 4. İş Zekası ve Veri Madenciliği (Weka ile), Şadi Evren Şeker, Cinius Yayınevi, 2013. 5. Data Mining: Concepts and Techniques, Jiawei Han, Micheline Kamber,Morgan Kaufmann Publishers, 2006 6. Introduction to Data Mining, Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Pearson, 2006

ASSESSMENT CRITERIA


If any,

mark as (X) Percent

(%)

If any, mark as (X)

Percent (%)



Homework Term Paper


Oral Examination



Other

Week Subjects

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Data, Information, Knowledge, Wisdom Concepts Knowledge Discovery in Databases Data Mining Methods Classifying Clustering Association Analysis Introduction to Text Mining Natural Language Processing Information Retrieval Information Extraction Application with RapidMiner Application with Weka Presentations General Reviews

Instructor/s Asist. Prof. Dr. Kadriye ERGÜN



Documents

GRADUATE COURSE DETAILS - fbe.balikesir.edu.trfbe.balikesir.edu.tr/fbe/docs/dersicerikleri/en/endmuh_en.pdf · Taha H.A., Yöneylem Araştırması, Literatür Yayıncılık, 2000