ECTSOptimization Applications in Manufacturing Systems

Optimization Applications in Manufacturing Systems (MFGE579) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Optimization Applications in Manufacturing Systems MFGE579 Elective Courses 2 2 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses Taken From Other Departments
Course Level Ph.D.
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture, Drill and Practice, Problem Solving.
Course Coordinator
Course Lecturer(s)
  • Asst. Prof. Dr. Celalettin Karadoğan
Course Assistants
Course Objectives To acquaint students with the fundamentals of stochastic simulations and nonlinear optimization. To give information about the application of stochastic methods for the process stability and process robustness. Familiarize the students about the methods of nonlinear optimization for complex production systems.
Course Learning Outcomes The students who succeeded in this course;
  • Students will realize the problem of nonlinear optimization and stochastic process optimization.
  • Mathematical fundamentals of nonlinear process optimization will be introduced.
  • Optimization of topology, form and material. Optimization of metal forming systems pertaining to workpiece tolerances and tool loading
  • Introduction to stochastic nature and robustness of processes
  • Stochastic modeling of manufacturing systems in car body production – LS-OPT
Course Content Introduction to the nonlinear optimization and stochastic process modeling, mathematical fundamentals of nonlinear process optimization, structure optimization: topology, form and material, introduction to nonlinear finite elements, optimization of manufacturing systems with regard to tolerances and tool loadings, pptimization of dynamical systems,

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Chapter 1: Introduction to the nonlinear optimization and stochastic process modeling
2 Chapter 2: Mathematical fundamentals of nonlinear process optimization
3 Chapter 3: Structure optimization: topology, form and material
4 Chapter 4: Introduction to nonlinear finite elements
5 Chapter 5: Optimization of manufacturing systems with regard to tolerances and tool loadings
6 Chapter 6: Optimization of dynamical systems
7 Chapter 7: Introduction to process robustness and stochasticity
8 Chapter 8: Virtual modeling of stochastic systems
9 Chapter 9: Virtual modeling of stochastic systems
10 Chapter 10: Introduction to design of experiments
11 Chapter 11: Design optimization with robustness analysis
12 Chapter 12: Stochastic modeling of manufacturing systems in car body production
13 Chapter 13: Optimization codes; OPTIS, ST-ORM and LS-OPT
14 Chapter 14: Optimization codes; OPTIS, ST-ORM and LS-OPT
15 Final Examination Period
16 Final Examination Period

Sources

Course Book 1. Masataka Yoshimura, System Design Optimization for Product Manufacturing, Springer, 2010
Other Sources 2. J. George Shanthikumar, David D. Yao, and W. Henk M. Zijm: Stochastic Modeling and Optimization of Manufacturing Systems and Supply Chains, Springer, 2003
3. Robert F. Rhyder: Manufacturing Process Design and Optimization; Marcel Dekker, 1997.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 6 30
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 30
Final Exam/Final Jury 1 40
Toplam 8 100
Percentage of Semester Work 60
Percentage of Final Work 40
Total 100

Course Category

Core Courses
Major Area Courses X
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Gains the ability to understand and apply knowledge in the fields of mathematics, science and basic sciences at the level of expertise.
2 Gains the ability to access wide and deep knowledge in the field of Engineering by doing scientific research with current techniques and methods, evaluate, interpret and implement the gained knowledge.
3 Being aware of the latest developments his/her field of study, defines problems, formulates and develops new and/or original ideas and methods in solutions.
4 Designs and applies theoretical, experimental, and model-based research, analyzes and interprets the results obtained at the level of expertise.
5 Gains the ability to use the applications, techniques, modern tools and equipment in his/her field of study at the level of expertise.
6 Designs, executes and finalizes an original work process independently.
7 Can work in interdisciplinary and interdisciplinary teams, lead teams, use the information of different disciplines together and develop solution approaches.
8 Pays regard to scientific, social and ethical values in all professional activities and acquires responsibility consciousness at the level of expertise.
9 Contributes to the literature by communicating the processes and results of his/her academic studies in written form or orally in national and international academic environments, communicates effectively with communities and scientific staff working in the field of specialization.
10 Gains the skill of lifelong learning at the level of expertise.
11 Communicates verbally and in written form using a foreign language at least at the European Language Portfolio B2 General Level.
12 Recognizes the social, environmental, health, safety, legal aspects of engineering applications, as well as project management and business life practices, being aware of the limitations they place on engineering applications.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours)
Laboratory
Application 16 2 32
Special Course Internship
Field Work
Study Hours Out of Class 16 6 96
Presentation/Seminar Prepration
Project
Report
Homework Assignments 6 6 36
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury
Prepration of Final Exams/Final Jury 1 15 15
Total Workload 179