Advanced Topics in Quality Engineering (IND 523)

Content

Objective

The aim of this course is to provide students with a basic understanding of the approaches, systems and techniques to assess and improve product/service quality in a manufacturing/service organization. The principles and techniques of experimental design and Six Sigma methodology and their practical implementation issues in product and service realization are introduced. Quality Systems and Management in both the manufacturing and servicing environment with strong emphasis on development of quality management systems and application of Total Quality Management (TQM) concepts to enhance organizational competitiveness are discussed.

Course Content

1. week : Product and service quality dimensions
2. week : Modern Quality Management development and background
3. week : Basic statistics and probabilities for quality and reliability
4. week : Statistical Process Control, Control Charts for Variables
5. week : Introduction to experimental design
6. week : Experiments with a single factor: the analsis of variance
7. week : Introduction to factorial designs
8. week : Blocking and confounding in the 2k factorial design
9. week : Mid term
10. week : Response surface models
11. week : Quality function deployment, voice of the customer
12. week : Six Sigma and DMAIC methodology
13. week : Case studies
14. week : Case studies

Course Learning Outcomes

Upon successful completion of this course, students should be able to:
1. Define the various dimensions of quality in product and service realization.
2. Outline the evolution and principles of modern quality management theories and practices.
3. Describe the framework and associated issues of implementing TQM systems in the organizations.
4. Understand quality and reliability concept.
6. Design a simple sampling plan, construct its OC curve and evaluate its effectiveness for a given process.
7. Acquire some basics of the experimental design and its application.

Teaching and Learning Methods

Lecture, discussion, case study.

References

• Montgomery, D.C., Design and Analysis of Experiments, Sixth Edition, John Wiley & Sons, 2005.
• Besterfield D.H. et al, Total Quality Management, Prentice-Hall, Englewood, USA, 2003.
• Gryna F.M., Chua C.H., DeFeo J.A., Juran’s Quality Planning and Analysis, 5th edition, McGraw-Hill, 2007.

Weekly Contents

Theory Topics
Week	Weekly Contents
1	Product and service quality dimensions
2	Modern Quality Management development and background
3	Basic statistics and probabilities for quality and reliability
4	Statistical Process Control, Control Charts for Variables
5	Introduction to experimental design
6	Experiments with a single factor: the analsis of variance
7	Introduction to factorial designs
8	Blocking and confounding in the 2k factorial design
9	Mid term
10	Response surface models
11	Quality function deployment, voice of the customer
12	Six Sigma and DMAIC methodology
13	Case studies
14	Case studies

Assessment System

Contribution to Overall Grade
Activities	Number	Contribution
Contribution of in-term studies to overall grade	1	60
Contribution of final exam to overall grade	1	40
Total	2	100

In-Term Studies
Activities	Number	Contribution
Assignments	0	0
Presentation	1	30
Midterm Examinations (including preparation)	1	30
Project	0	0
Laboratory	0	0
Other Applications	0	0
Quiz	0	0
Term Paper/ Project	0	0
Portfolio Study	0	0
Reports	0	0
Learning Diary	0	0
Thesis/ Project	0	0
Seminar	0	0
Other	0	0
Total	2	60

Relation of Proficiency

No	Program Learning Outcomes	Contribution
No	Program Learning Outcomes	1	2	3	4	5
1					X
2						X
3						X
4					X
5						X
6						X
7						X
8				X
9						X
10					X
11				X
12				X

ECTS

Activities	Number	Period	Total Workload
Class Hours	14	3	42
Working Hours out of Class	13	5	65
Presentation	1	20	20
Midterm Examinations (including preparation)	1	15	15
Final Examinations (including preparation)	1	20	20
Total Workload			162
Total Workload / 25			6.48
Credits ECTS			6