| Course Title | Code | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|
| Statistics and Optimization | MEM387 | 5. Semester | 2 + 0 | 2.0 | 3.0 |
| Prerequisites | None |
| Language of Instruction | Turkish |
| Course Level | Undergraduate |
| Course Type | |
| Mode of delivery | Face to face |
| Course Coordinator |
Assoc. Prof. Dr. Gürcan SAMTAŞ |
| Instructors | |
| Assistants | |
| Goals | • Utilize statistical tools to analyze and interpret sensor data. • Apply statistical distributions to model the behavior of mechatronic systems. • Optimize error estimation and decision-making processes in control systems. • Enhance the performance of mechatronic systems by optimizing design parameters. • Develop data-driven decision making and statistical thinking for engineering problem solving. |
| Course Content | This course introduces critical statistical and optimization techniques for solving problems frequently encountered in Mechatronics Engineering. We aim to equip students with the ability to utilize statistical methods for data analysis, modeling, and decision-making processes, as well as mathematical tools to optimize design and control problems. |
| Learning Outcomes |
- Calculate statistical properties of data acquired from sensors. - Employ statistical methods to analyze and filter noisy signals. - Utilize statistical distributions to model the dynamic behavior of mechatronic systems. - Perform error estimation and design decision rules in control systems. - Apply linear programming and other optimization techniques to optimize design parameters. - Interpret statistical results to evaluate and improve the performance of mechatronic systems. |
| Week | Topics | Learning Methods |
|---|---|---|
| 1. Week | Introduction & Sensor Data | Research Visual Presentation Preparation, After Class Study Verbal Expression Other Activities Practice Course Hours |
| 2. Week | Probability & Random Variables | Other Activities Verbal Expression Practice Preparation, After Class Study Course Hours Research Visual Presentation |
| 3. Week | Statistical Distributions & Mechatronic Systems | Practice Course Hours Verbal Expression Preparation, After Class Study Other Activities Visual Presentation Research |
| 4. Week | Error Estimation & Control Systems | Preparation, After Class Study Practice Visual Presentation Research Verbal Expression Course Hours Other Activities |
| 5. Week | Linear Regression & Mechatronics Applications | Practice Other Activities Verbal Expression Visual Presentation Research Preparation, After Class Study Course Hours |
| 6. Week | Linear Regression & Mechatronics Applications | Practice Other Activities Visual Presentation Research Preparation, After Class Study Course Hours Verbal Expression |
| 7. Week | Linear Programming & Design Optimization | Verbal Expression Other Activities Practice Preparation, After Class Study Visual Presentation Research Course Hours |
| 8. Week | Linear Programming & Design Optimization | Course Hours Practice Verbal Expression Research Preparation, After Class Study Other Activities Visual Presentation |
| 9. Week | Other Optimization Techniques | |
| 10. Week | Other Optimization Techniques | |
| 11. Week | Sampling Methods & Mechatronics Applications | |
| 12. Week | Advanced Statistical Techniques for Mechatronics | Course Hours Preparation, After Class Study Visual Presentation Verbal Expression Research Practice Other Activities |
| 13. Week | Optimization Algorithms & Mechatronics Applications | Preparation, After Class Study Research Verbal Expression Other Activities Practice Visual Presentation Course Hours |
| 14. Week | Optimization Algorithms & Mechatronics Applications | Verbal Expression Practice Other Activities Visual Presentation Research Course Hours Preparation, After Class Study |
| • Mühendisler İçin Uygulamalı İstatistik ve Olasılık, Douglas C. Montgomery , George C. Runger, Palme Yayınevi |
| Program Requirements | Contribution Level | DK1 | DK2 | DK3 | DK4 | DK5 | DK6 | Measurement Method |
|---|
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| Course's Level of contribution | None | Very Low | Low | Fair | High | Very High |
| Method of assessment/evaluation | Written exam | Oral Exams | Assignment/Project | Laboratory work | Presentation/Seminar |
| Event | Quantity | Duration (Hour) | Total Workload (Hour) |
|---|---|---|---|
| Midterm 1 | 50 | 1 | 50 |
| Final | 26.5 | 1 | 26.5 |
| Total Workload | 76.5 | ||
| ECTS Credit of the Course | 3.0 | ||
