COURSE UNIT TITLE

: STATISTICAL THINKING AND SIX SIGMA

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
UKY 8044 STATISTICAL THINKING AND SIX SIGMA ELECTIVE 3 0 0 5

Offered By

Quality Management Non-thesis (Distance Learning)

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR GÜLÜZAR KURT GÜMÜŞ

Offered to

Quality Management Non-thesis (Distance Learning)

Course Objective

the objective of this course is explain definiation, history, evoluation, essentials, benefits and terminology of six sigma, and present the similarities and differences between six sigma and other quality systems

Learning Outcomes of the Course Unit

1   to be able to explain six sigma concepts
2   to be able to improve processes by six sigma
3   to be able to make decisions based on data and realities
4   to be able to minimize defects
5   to be able to improve processes continuously

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 six sigma process
2 1.5 sigma shifting
3 design for six sigma (DFSS)
4 personnel requirements for six sigma projects (sponsor, champion)
5 personnel requirements for six sigma projects (expert black belt, black belt, green belt, yellow belt)
6 DMAIC- define and measure stages
7 DMAIC - analysis, improvement and control stages
8 six sigma process
9 six sigma sucsess factors
10 six sigma and total quality management / lean six sigma
11 project presentations
12 project presentations
13 project presentations
14 project presentations

Recomended or Required Reading

PYZDEK, T. ve KELLER P. (2009) The Six Sigma Hand Book, 3th Edition, McGraw-Hill, New York
HAYLER, R. ve NICHOLS, M. (2005) What is Six Sigma Process Management, Mc Graw Hill, NY

Planned Learning Activities and Teaching Methods

1- Class Lecturing , 2- Lectures on applications , 3- Presentations of Case Studies,
4- Discussion and analysis of case studies

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FCG FINAL COURSE GRADE
3 FCGR FINAL COURSE GRADE MTE * 0.40 + FCG* 0.60
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + RST* 0.60


Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 2 28
Preparation for final exam 1 10 10
Preparation for midterm exam 1 10 10
Preparing presentations 2 10 20
Preparations before/after weekly lectures 14 3 42
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 114

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6
LO.144455
LO.244455
LO.3444535
LO.444455
LO.544455