Master's Degree in Industrial Engineering with Thesis
Course Details
KTO KARATAY UNIVERSITY
Graduate Education Institute
Programme of Master's Degree in Industrial Engineering with Thesis
Course Details
Graduate Education Institute
Programme of Master's Degree in Industrial Engineering with Thesis
Course Details
| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 84211117 | Experimental Design and Analysis | 1 | Autumn | 1 | 3+0+0 | 7 | 7 |
| Course Type | Elective |
| Course Cycle | Master's (Second Cycle) (TQF-HE: Level 7 / QF-EHEA: Level 2 / EQF-LLL: Level 7) |
| Course Language | Turkish |
| Methods and Techniques | - |
| Mode of Delivery | Face to Face |
| Prerequisites | - |
| Coordinator | - |
| Instructor(s) | Asst. Prof. Şule ERYÜRÜK |
| Instructor Assistant(s) | - |
Course Instructor(s)
| Name and Surname | Room | E-Mail Address | Internal | Meeting Hours |
|---|---|---|---|---|
| Asst. Prof. Şule ERYÜRÜK | A-306 | [email protected] | 7537 |
Course Content
This course covers experimental design and analysis techniques used in scientific research. Students will learn how to plan and conduct experiments, and how to analyze their results. Topics include factorial designs, randomized block designs, response surface methodology, and analysis of variance. This course helps students develop their skills in using scientific methodologies in experimental research and in accurately analyzing data. This course will enable students to conduct their scientific research more systematically and reliably.
Objectives of the Course
The objective of this course is to enable students to effectively apply experimental design and analysis methods used in scientific research. This course will equip students with the skills to plan and conduct experiments and to analyze the resulting data using appropriate statistical techniques. This will equip them to conduct scientific research in a more systematic, reliable, and valid manner.
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 |
|---|---|---|
| P1 | Using scientific research methods in the field of Industrial Engineering, they access information in depth and from a broad perspective; they critically analyze, interpret, and apply the information they obtain. | 5 |
| P2 | Possesses advanced knowledge of current methods, techniques, and tools used in Industrial Engineering, as well as the assumptions and limitations of these approaches. | 5 |
| P3 | In situations where data is uncertain, incomplete, or limited in the field of Industrial Engineering, they supplement information using scientific and analytical methods; they develop solutions by integrating information obtained from different disciplines. | 5 |
| P4 | Monitors new and emerging applications, approaches, and technologies in the field of Industrial Engineering; develops and manages the learning process in these areas as needed. | 3 |
| P5 | Industrial Engineering systematically defines problems; develops appropriate models and methods for these problems and applies innovative approaches in the solution processes. | 5 |
| P6 | Yeni ve özgün fikirler üreterek karmaşık sistem ve süreçlerin tasarımını gerçekleştirir; alternatif ve yenilikçi çözüm önerileri geliştirir. | 3 |
| P7 | Plans and conducts theoretical, experimental, and/or modeling-based research; analyzes and resolves complex problems encountered during the research process. | 5 |
| P8 | Effectively participates in intra-disciplinary and interdisciplinary teams; assumes leadership when necessary, develops solution-oriented approaches using project and risk management tools; can work independently and take responsibility. | 3 |
| P9 | They present the processes and results of their work in a clear, systematic, and understandable manner, both in writing and/or orally, in national and international academic or professional settings; they act in accordance with entrepreneurship, innovation, sustainability, and social and ethical values in professional practice. | 3 |
| P10 | Entrepreneurship, innovation, and sustainability can be implemented in business practices. | 2 |
| P11 | It observes social, scientific, and ethical values during the collection, interpretation, and dissemination of data, as well as in all professional activities. | 3 |
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | Introduction to Design of Experiments and Basic Concepts |
| 2 | Statistical Foundations and Assumptions |
| 3 | Experimental Error, Randomization, and Replication |
| 4 | Single-Factor Experimental Designs |
| 5 | Analysis of Variance (ANOVA) |
| 6 | Multiple Comparison Tests |
| 7 | Full Factorial Experimental Designs |
| 8 | Midterm |
| 9 | Fractional Factorial Experimental Designs |
| 10 | Interaction Effects and Graphical Analysis |
| 11 | Blocking and Mixed Experimental Designs |
| 13 | Regression-Based Experimental Analysis |
| 14 | Applications of Design of Experiments in Industrial Engineering |
| 15 | Presentations and Case Analyses |
Textbook or Material
| Resources | Industrial Design of Experiments: A Case Study Approach for Design and Process Optimization – Sammy Shina |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Homework | - | - |
| Presentation | - | - |
| 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 | 13 | 13 |
| Quiz | 0 | 0 | 0 |
| Homework | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Project | 1 | 30 | 30 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 4 | 15 | 60 |
| Fieldwork | 2 | 15 | 30 |
| Final Exam | 0 | 0 | 0 |
| Other | 4 | 2 | 8 |
| Total Work Load: | 225 | ||
| Total Work Load / 30 | 7,50 | ||
| Course ECTS Credits: | 8 | ||