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 |
|---|---|---|---|---|---|---|---|
| 05580002 | Intelligent Mechatronics Systems | 4 | Spring | 8 | 2+1+0 | 4 | 4 |
| Course Type | Compulsory |
| 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, Project, Presentation |
| Mode of Delivery | Face to Face |
| Prerequisites | There is no prerequisite for the course. |
| Coordinator | - |
| Instructor(s) | Asst. Prof. Hüseyin ALP |
| Instructor Assistant(s) | Res. Asst. Sinan İLGEN |
Course Instructor(s)
| Name and Surname | Room | E-Mail Address | Internal | Meeting Hours |
|---|---|---|---|---|
| Asst. Prof. Hüseyin ALP | - | [email protected] |
Course Content
Existing models of basic principles of intelligent systems, Complex engineering systems, control and recognition. Intelligent control approaches. Possible technologies: soft computing, traditional methods and information theory; data management applications, sensor fusion, control systems, diagnostic/prediction systems, fault tolerant control and supervised control. Application areas: textile and fibre processing, pulp and paper, aerospace and automotive systems, etc. Artificial Neural Networks (ANN), Fuzzy Logic (FL), Genetic Algorithms (GA). Use of ANN, FL and GA in control, prediction, planning, diagnosis, imaging and heuristic search methods.
Objectives of the Course
This course aims to the students to use and develop intelligent mechatronics systems.
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 |
| P3 | Ability to design a complex system, process, device, or product to meet specific requirements under realistic constraints and conditions; ability to apply modern design methods for this purpose | 5 |
| P6 | Ability to work effectively in disciplinary and multi-disciplinary teams; individual working skills | 5 |
Course Learning Outcomes
| Upon the successful completion of this course, students will be able to: | |||
|---|---|---|---|
| No | Learning Outcomes | Outcome Relationship | Measurement Method ** |
| O1 | Ability to have up-to-date knowledge about the applications of intelligent mechatronic systems in the fields of system interface, instrumentation and control | P.2.4 | 1,5 |
| O2 | Ability to have up-to-date knowledge about the applications of intelligent mechatronic systems in the field of robotics | P.2.5 | 1,5 |
| O3 | Ability to develop intelligent control algorithms for mechatronic systems | P.3.4 | 7 |
| O4 | Ability to have up-to-date knowledge about physical system modelling and real-time applications of intelligent mechatronic systems | P.3.5 | 1,5 |
| O5 | Ability to make effective presentations and write reports on a given topic | P.6.3 | 5 |
| ** 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 |
| 2 | Mechatronics and intelligent systems |
| 3 | Complex engineering systems, control and recognition |
| 4 | Intelligent control approaches |
| 5 | Possible technologies: easy calculation (Soft computing), conventional methods and information theory data management applications |
| 6 | Possible technologies: easy calculation (Soft computing), conventional methods and information theory data management applications |
| 7 | Sensor fusion, control systems, diagnosis / prediction systems, fault-tolerant control and supervised control. |
| 8 | Sensor fusion, control systems, diagnosis / prediction systems, fault-tolerant control and supervised control. |
| 9 | Artificial intelligence |
| 10 | Artificial intelligence |
| 11 | Neural Networks and fuzzy systems |
| 12 | Genetic Algorithms (GA). The use of ANN, FL and GA in control |
| 13 | Estimation, planning, diagnosis, imaging, and heuristic search methods. |
| 14 | Application fields: textile and fiber processing, pulp and paper, aerospace and automotive systems |
Textbook or Material
| Resources | D.A. Bradley, D. Dawson, D. Seward, S. Burge "Mechatronics and the Design of Intelligent Machines and Systems", CRC Press Inc (2000) |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Laboratory | - | - |
| Practice | - | - |
| Course Specific Internship (If Any) | - | - |
| Homework | - | - |
| Presentation | - | - |
| Projects | 1 | 35 (%) |
| Quiz | - | - |
| Midterms | 1 | 30 (%) |
| Final Exam | 1 | 35 (%) |
| Total | 100 (%) | |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 14 | 2 | 28 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 14 | 3 | 42 |
| Midterms | 1 | 15 | 15 |
| Quiz | 0 | 0 | 0 |
| Homework | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Project | 1 | 10 | 10 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 1 | 10 | 10 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 1 | 15 | 15 |
| Other | 0 | 0 | 0 |
| Total Work Load: | 120 | ||
| Total Work Load / 30 | 4 | ||
| Course ECTS Credits: | 4 | ||
Course - Learning Outcomes Matrix
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Learning Outcomes | P2 | P3 | P6 |
|---|---|---|---|---|
| O1 | Ability to have up-to-date knowledge about the applications of intelligent mechatronic systems in the fields of system interface, instrumentation and control | 5 | - | - |
| O2 | Ability to have up-to-date knowledge about the applications of intelligent mechatronic systems in the field of robotics | 5 | - | - |
| O3 | Ability to develop intelligent control algorithms for mechatronic systems | - | 5 | - |
| O4 | Ability to have up-to-date knowledge about physical system modelling and real-time applications of intelligent mechatronic systems | - | 5 | - |
| O5 | Ability to make effective presentations and write reports on a given topic | - | - | 5 |