Mechatronics Engineering
Course Details
KTO KARATAY UNIVERSITY
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Mechatronics Engineering
Course Details
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Mechatronics Engineering
Course Details
| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 05581012 | Optimization | 4 | Spring | 8 | 3+0+0 | 5 | 5 |
| Course Type | Elective |
| Course Cycle | Bachelor's (First Cycle) (TQF-HE: Level 6 / QF-EHEA: Level 1 / EQF-LLL: Level 6) |
| Course Language | Turkish |
| Methods and Techniques | Lecture |
| Mode of Delivery | Face to Face |
| Prerequisites | There is no prerequisite for the course |
| Coordinator | - |
| Instructor(s) | Asst. Prof. Esra URAY |
| Instructor Assistant(s) | - |
Course Instructor(s)
| Name and Surname | Room | E-Mail Address | Internal | Meeting Hours |
|---|---|---|---|---|
| Asst. Prof. Esra URAY | A-Z34 | [email protected] | 7312 |
Course Content
Solution methods for constrained, unconstrained, continuous and discrete optimisation problems
Objectives of the Course
The aim of this course is to recognize the optimization fundamentals and methods and to examine engineering optimization applications.
Contribution of the Course to Field Teaching
| Basic Vocational Courses | |
| Specialization / Field Courses | X |
| Support Courses | |
| Transferable Skills Courses | |
| Humanities, Communication and Management Skills Courses |
Relationships between Course Learning Outcomes and Program Outcomes
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Program Learning Outcomes | Level |
|---|---|---|
| P2 | Ability to identify, formulate and solve complex Mechatronics Engineering problems; ability to select and apply appropriate analysis and modeling methods for this purpose. | 5 |
| P4 | Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in Mechatronics Engineering applications; Ability to use information technologies effectively | 5 |
Course Learning Outcomes
| Upon the successful completion of this course, students will be able to: | |||
|---|---|---|---|
| No | Learning Outcomes | Outcome Relationship | Measurement Method ** |
| O1 | Gains general information about the concept of optimization, its elements and classification | P.2.56 | 1 |
| O2 | Creates an optimization design model for solving real problems encountered in engineering | P.2.57 | 1 |
| O3 | Determines the appropriate optimization method for solving an engineering problem, gains the ability to comment and design for the optimum solution of the problem | P.4.34 | 1 |
| O4 | Gains information on the simple use of appropriate software for solving an engineering optimization problem | P.4.35 | 1 |
| ** Written Exam: 1, Oral Exam: 2, Homework: 3, Lab./Exam: 4, Seminar/Presentation: 5, Term Paper: 6, Application: 7 | |||
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | Introduction to Optimization |
| 2 | Teaching the necessary software for optimization (MATLAB relational and logical operators and basic mathematical operations) |
| 3 | Teaching the necessary software for optimization (MATLAB loops and functions) |
| 4 | Teaching the necessary software for optimization (MATLAB array and matrix operations) |
| 5 | Teaching the necessary software for optimization (MATLAB graph drawing, graph types and graphical optimization) |
| 6 | Teaching the necessary software for optimization (MATLAB and EXCEL optimization applications) |
| 7 | MATLAB Applications |
| 8 | Midterm |
| 9 | Unconstrained Optimisation |
| 10 | Constrained Optimization |
| 11 | Heuristic optimization algorithms |
| 12 | Heuristic optimization algorithms |
| 13 | Student project presentations on heuristic optimisation algorithms |
| 14 | Student project presentations on heuristic optimisation algorithms |
Textbook or Material
| Resources | INTRODUCTION TO OPTIMUM DESIGN, JASBIR S. ARORA, Elsevier |
| Optimizasyon ve Matlab Uygulamaları, Aysun Tezel Özturan, Nobel Akademik Yayıncılık | |
| Optimizasyon ve Matlab Uygulamaları, Aysun Tezel Özturan, Nobel Akademik Yayıncılık Ders Notları |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Laboratory | - | - |
| Practice | - | - |
| Course Specific Internship (If Any) | - | - |
| Homework | - | - |
| Presentation | - | - |
| Projects | - | - |
| Quiz | - | - |
| Midterms | 1 | 40 (%) |
| Final Exam | 1 | 60 (%) |
| Total | 100 (%) | |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 14 | 3 | 42 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 14 | 3 | 42 |
| Midterms | 1 | 20 | 20 |
| Quiz | 0 | 0 | 0 |
| Homework | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Workshop | 1 | 10 | 10 |
| Presentation/Seminar Preparation | 1 | 5 | 5 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 1 | 20 | 20 |
| Other | 0 | 0 | 0 |
| Total Work Load: | 139 | ||
| Total Work Load / 30 | 4,63 | ||
| Course ECTS Credits: | 5 | ||
Course - Learning Outcomes Matrix
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Learning Outcomes | P2 | P4 |
|---|---|---|---|
| O1 | Gains general information about the concept of optimization, its elements and classification | 5 | - |
| O2 | Creates an optimization design model for solving real problems encountered in engineering | 5 | - |
| O3 | Determines the appropriate optimization method for solving an engineering problem, gains the ability to comment and design for the optimum solution of the problem | - | 5 |
| O4 | Gains information on the simple use of appropriate software for solving an engineering optimization problem | - | 5 |