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
  IE 234 To succeed (To get a grade of at least DD)
or MATH 236 To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Required
Course Level
First Cycle
Mode of Delivery face to face
Teaching Methods and Techniques of the Course Problem Solving
Lecture / 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;
  • Will be able to describe what quality is and the methods to improve quality through design and control
  • Will be able to apply statistical methods and probability concepts for data characterization
  • Will be able to explain sampling distributions and statistical hypothesis testing
  • Will be able to apply control chart techniques for quality improvement
  • Will be able to apply tolerance and process capability assessment
  • Will be able to analyze reliability data
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.

 



Course Category

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.

11

To be able to collect data in the area of Industrial Engineering; to be able to communicate with colleagues in a foreign language.

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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