FACULTY OF ENGINEERING

Department of Industrial Engineering

IE 334 | Course Introduction and Application Information

Course Name
Statistical Quality Control
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
IE 334
Spring
2
2
3
7

Prerequisites
  IE 240 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
Application: Experiment / Laboratory / Workshop
Lecture / Presentation
Course Coordinator
Course Lecturer(s)
Assistant(s) -
Course Objectives This course aims to provide knowledge in quality costs, basic concepts, tools and statistical techniques for quality control.
Learning Outcomes The students who succeeded in this course;
  • Analyze quality costs
  • Apply statistical methods for data characterization
  • Use problem identification tools
  • Apply control charts to improve quality
  • Perform process capability and measurement system analysis
  • Solve quality problems using statistical experimental design
Course Description This course covers; quality costs and analysis, statistical methods (confidence intervals, hypothesis testing, analysis of variance), problem identification tools, control charts for variables and attributes, process capability analysis, measurement system analysis, statistical experimental design.

 



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 Quality Concept and Quality Costs Montgomery, D.C., Introduction to Statistical Quality Control (7th Edition), Chapter 1, 3-47
2 Statistical Models for Data Characterization Montgomery, D.C., Introduction to Statistical Quality Control (7th Edition), Chapter 3, 67-79
3 Statistical Models for Data Characterization Montgomery, D.C., Introduction to Statistical Quality Control (7th Edition), Chapter 3, 80-102
4 Inferences About Process Quality Montgomery, D.C., Introduction to Statistical Quality Control (7th Edition), Chapter 4, 117-150
5 Statistical Basis of the Control Chart, Problem Identification Tools Montgomery, D.C., Introduction to Statistical Quality Control (7th Edition), Chapter 5, 187-210
6 Control Charts for Variables Montgomery, D.C., Introduction to Statistical Quality Control (7th Edition), Chapter 6, 234-258
7 Control Charts for Variables Montgomery, D.C., Introduction to Statistical Quality Control (7th Edition), Chapter 6, 259-276
8 Control Charts for Attributes Montgomery, D.C., Introduction to Statistical Quality Control (7th Edition), Chapter 7, 297-316
9 Midterm Exam
10 Control Charts for Attributes Montgomery, D.C., Introduction to Statistical Quality Control (7th Edition), Chapter 7, 317-339 7, 2
11 Process Capability Analysis Montgomery, D.C., Introduction to Statistical Quality Control (7th Edition), Chapter 8, 355-378
12 Measurement System Analysis Montgomery, D.C., Introduction to Statistical Quality Control (7th Edition), Chapter 8, 379-395
13 Introduction to Statistical Experimental Design Montgomery, D.C., Introduction to Statistical Quality Control (7th Edition), Chapter 13, 563-569
14 Factorial Designs Montgomery, D.C., Introduction to Statistical Quality Control (7th Edition), Chapter 13, 570-590
15 Review semester
16 Final Exam

 

Course Notes/Textbooks

Montgomery, D.C., Introduction to Statistical Quality Control-A Modern Introduction, Wiley, 7th Edition, 2013, ISBN: 9781118322574

Suggested Readings/Materials

Montgomery, D.C., Design and Analysis of Experiments, Wiley, 8th Edition, 2013, ISBN: 9781118097939.

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
1
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
5
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
10
30
Portfolio
0
Homework / Assignments
0
Presentation / Jury
0
Project
0
Seminar / Workshop
0
Oral Exam
0
Midterms
1
25
25
Final Exam
1
35
35
    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.

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.

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.

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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