FACULTY OF ENGINEERING

Department of Industrial Engineering

IE 327 | Course Introduction and Application Information

Course Name
Special Topics in Production Management
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
IE 327
Fall/Spring
3
0
3
6

Prerequisites
  MATH 236 To succeed (To get a grade of at least DD)
Course Language
English
Course Type
Elective
Course Level
First Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course Group Work
Lecture / Presentation
Course Coordinator
Course Lecturer(s)
Assistant(s) -
Course Objectives The aim of the course is to introduce different process improvement approaches, especially the Lean Six Sigma project approach. Process diagramming, statistical analysis techniques, hypothesis tests and some graphical analyzes are covered by this course.
Learning Outcomes The students who succeeded in this course;
  • • Will be able to understand basic project management approach of Six Sigma
  • • Will be able to understand how the five basic steps of Six Sigma can be used for both in the project management and process improvement
  • • Will be able to evaluate how manufacturing process can be improved by using some statistical tools
  • • Will be able to understand how hypothesis tests are used to solve real production problems
  • • Will be able to improve their problems with statistical tools by taking a process based approach.
  • Will be able to distinguish the suitability of the techniques used in the Six Sigma approach
Course Description The history of the Six Sigma approach and its diffusion in the world, examples of applications in the world and in Turkey, basic steps of the Six Sigma project management approach, statistical and managerial tools used at each step and best practices for use of these tools constitute the course content.

 



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 History of Six Sigma Slides of week
2 Six Sigma Project Management Approach Slides of week
3 DMAIC Slides of week
4 Project Chart and Definiton Tools Slides of week
5 SIPOC, VOC and VOB Slides of week
6 Group Case Study Slides of week
7 Measurement System Analysis-1 Slides of week
8 Measurement System Analysis-2 Slides of week
9 Hypothetical Tests Slides of week
10 Graphical Analysis Slides of week
11 Comparison of Mean Values Slides of week
12 Comparison of Proportions Slides of week
13 Regression and Correlation Slides of week
14 Statistical Process Control Slides of week
15 Group Presentation Slides of week
16 Final Exam

 

Course Notes/Textbooks

G. Robin Henderson (2011). Six Sigma Quality Improvement with Minitab, Wiley.

Rehman M. Khan (2013). Problem Solving and Data Analysis Using Minitab, Wiley.

Pande, P. S., Neuman, R. P., & Cavanagh, R. R. (2000). The Six Sigma Way. New York: McGraw-Hill, ML, George, Rowlands D, Price M, and Maxey J. The Lean Six Sigma Pocket Toolbook. McGraw Hill Co, 2005.

Suggested Readings/Materials Lecture PowerPoint slides,Reading materials, scientific papers and handouts.

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
10
20
Laboratory / Application
2
20
Field Work
Quizzes / Studio Critiques
3
15
Portfolio
Homework / Assignments
2
20
Presentation / Jury
Project
1
25
Seminar / Workshop
Oral Exams
Midterm
Final Exam
Total

Weighting of Semester Activities on the Final Grade
100
Weighting of End-of-Semester Activities on the Final Grade
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
0
Study Hours Out of Class
14
5
70
Field Work
0
Quizzes / Studio Critiques
3
6
18
Portfolio
0
Homework / Assignments
2
11
22
Presentation / Jury
0
Project
1
22
22
Seminar / Workshop
0
Oral Exam
0
Midterms
0
Final Exam
0
    Total
180

 

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.

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.

X
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.

X

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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