
FACULTY OF ENGINEERING
Department of Industrial Engineering
IE 334 | Course Introduction and Application Information
Course Name |
Quality Assurance and Reliability
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
IE 334
|
Spring
|
2
|
2
|
3
|
7
|
Prerequisites |
|
|||||||||
Course Language |
English
|
|||||||||
Course Type |
Required
|
|||||||||
Course Level |
First Cycle
|
|||||||||
Mode of Delivery | face to face | |||||||||
Teaching Methods and Techniques of the Course | Problem SolvingLecture / Presentation | |||||||||
Course Coordinator | ||||||||||
Course Lecturer(s) | ||||||||||
Assistant(s) |
Course Objectives | This course aims to provide knowledge in basic models and techniques for quality assurance and reliability. Topics include sampling, hypothesis testing, Shewhart control charts, Xbar and R control charts, process capability, tolerance and reliability. |
Learning Outcomes |
The students who succeeded in this course;
|
Course Description | Quality concept, historical development of quality, quality costs, statistical data analyses, introduction to six sigma, problem solving tools, control charts for variables, control charts for attributes, process capability analysis, measurement system analysis, reliability analysis. |
|
Core Courses | |
Major Area Courses |
X
|
|
Supportive Courses | ||
Media and Management Skills Courses | ||
Transferable Skill Courses |
WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES
Week | Subjects | Related Preparation |
1 | Introduction to Quality Management and Improvement | Montgomery, Chapter 1 |
2 | Quality Costs | Montgomery, Chapter 2 |
3 | Statistical Models and Probability Concepts for Data Characterization | Montgomery, Chapter 3.1, 3.2 |
4 | Statistical Models and Probability Concepts for Data Characterization | Montgomery, Chapter 3.3, 3.4,3.5 |
5 | Inferences About Process Quality: Problem Identification and Solving Tools | Montgomery, Chapter 4.3, 4.4., 4.5, 4.6 |
6 | Statistical Basis of the Control Chart | Montgomery, Chapter 5 |
7 | Statistical Basis of the Control Chart | Montgomery, Chapter 5 |
8 | Control Charts for Variable Data | Montgomery, Chapter 6 |
9 | Control Charts for Variable Data | Montgomery, Chapter 6 |
10 | Attributes Control Charts | Montgomery, Chapter 7.1, 7, 2 |
11 | Attributes Control Charts | Montgomery, Chapter 7.3, 7.4, 7.5 |
12 | Process Capability Assessment | Montgomery, Chapter 8.1, 8.2, 8.3, 8.4 |
13 | Measurement System Analysis | Montgomery, Chapter 8.7 |
14 | Reliability | Lecture notes |
15 | Review semester | |
16 | Final sınavı |
Course Notes/Textbooks | Montgomery, D.C., Introduction to Statistical Quality Control, John Wiley and Sons Co., 7th Edition, 2013. |
Suggested Readings/Materials | Course Notes and Slides |
EVALUATION SYSTEM
Semester Activities | Number | Weigthing |
Participation | ||
Laboratory / Application |
4
|
20
|
Field Work | ||
Quizzes / Studio Critiques |
3
|
15
|
Portfolio | ||
Homework / Assignments | ||
Presentation / Jury | ||
Project | ||
Seminar / Workshop | ||
Oral Exams | ||
Midterm |
1
|
25
|
Final Exam |
1
|
40
|
Total |
Weighting of Semester Activities on the Final Grade |
8
|
60
|
Weighting of End-of-Semester Activities on the Final Grade |
1
|
40
|
Total |
ECTS / WORKLOAD TABLE
Semester Activities | Number | Duration (Hours) | Workload |
---|---|---|---|
Theoretical Course Hours (Including exam week: 16 x total hours) |
16
|
2
|
32
|
Laboratory / Application Hours (Including exam week: '.16.' x total hours) |
16
|
2
|
32
|
Study Hours Out of Class |
14
|
4
|
56
|
Field Work |
0
|
||
Quizzes / Studio Critiques |
3
|
7
|
21
|
Portfolio |
0
|
||
Homework / Assignments |
4
|
5
|
20
|
Presentation / Jury |
0
|
||
Project |
0
|
||
Seminar / Workshop |
0
|
||
Oral Exam |
0
|
||
Midterms |
1
|
19
|
19
|
Final Exam |
1
|
30
|
30
|
Total |
210
|
COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP
#
|
Program Competencies/Outcomes |
* Contribution Level
|
||||
1
|
2
|
3
|
4
|
5
|
||
1 | To have adequate knowledge in Mathematics, Science and Industrial Engineering; to be able to use theoretical and applied information in these areas to model and solve Industrial Engineering problems. |
X | ||||
2 | To be able to identify, formulate and solve complex Industrial Engineering problems by using state-of-the-art methods, techniques and equipment; to be able to select and apply proper analysis and modeling methods for this purpose. |
X | ||||
3 | To be able to analyze a complex system, process, device or product, and to design with realistic limitations to meet the requirements using modern design techniques. |
X | ||||
4 | To be able to choose and use the required modern techniques and tools for Industrial Engineering applications; to be able to use information technologies efficiently. |
X | ||||
5 | To be able to design and do simulation and/or experiment, collect and analyze data and interpret the results for investigating Industrial Engineering problems and Industrial Engineering related research areas. |
X | ||||
6 | To be able to work efficiently in Industrial Engineering disciplinary and multidisciplinary teams; to be able to work individually. |
X | ||||
7 | To be able to communicate effectively in Turkish, both orally and in writing; to be able to author and comprehend written reports, to be able to prepare design and implementation reports, to present effectively; to be able to give and receive clear and comprehensible instructions |
|||||
8 | To have knowledge about contemporary issues and the global and societal effects of Industrial Engineering practices on health, environment, and safety; to be aware of the legal consequences of Industrial Engineering solutions. |
|||||
9 | To be aware of professional and ethical responsibility; to have knowledge of the standards used in Industrial Engineering practice. |
X | ||||
10 | To have knowledge about business life practices such as project management, risk management, and change management; to be aware of entrepreneurship and innovation; to have knowledge about sustainable development. |
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11 | To be able to collect data in the area of Industrial Engineering; to be able to communicate with colleagues in a foreign language. |
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12 | To be able to speak a second foreign at a medium level of fluency efficiently. |
|||||
13 | To recognize the need for lifelong learning; to be able to access information, to be able to stay current with developments in science and technology; to be able to relate the knowledge accumulated throughout the human history to Industrial Engineering. |
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest
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