• HOME
• ABOUT US
  • Name Address
  • General Description
  • Governance
  • Academic Calendar
  • Degree Programmes
  • List of Programmes in English
  • General Admission and Registration Procedures
  • Credit Mobility and Recognition of Prior Learning
  • ECTS Credit Allocation
  • Academic Guidance
  • Contacts
• Degree Programmes
  • Third Cycle Programmes (Doctorate Degree)
  • Second Cycle Programmes (Master's Degree)
  • First Cycle Programmes (Bachelor's Degree)
  • Short Cycle Programmes (Associate's Degree)
• GENERAL INFORMATION FOR STUDENTS
  • Cost of Living
  • Accommodation
  • Meals
  • Medical Facilities
  • Facilities for Disabled Students
  • Insurance
  • Financial Supports
  • Student Affairs Office
  • Practical Information for International Students
  • Language Courses
  • Work Placement Possibilities
  • Sports, Social and Cultural Facilities
  • Student Associations and Clubs
  • About İzmir - Turkey
• INTERNATIONAL RELATIONS
  • International Relations Office
  • Registration Procedures
  • Agreements
  • Coordinators
  • Documents
  • List of Programmes in English
  • ECTS / DS Labels

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS TKY 7043 ADVANCED STATISTICAL IMPROVEMENT METHODS COMPULSORY 2 0 0 5

Offered By

Quality Management (Non-Thesis-Evening)

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR CENK ÖZLER

Offered to

Quality Management (Non-Thesis-Evening)

Course Objective

The aim of this course is to provide knowledge about statistical quality control techniques which include measurement system analysis for assessing measurement quality, experimental design for improvement of design quality, and advanced control charts.

Learning Outcomes of the Course Unit

1   to be able to design experiments for product/process design. 2   to be able to make statistical analyses about the results of experiments. 3   to be able to optimize the processes according to results of experiments. 4   to be able to analyze measurement systems. 5   to be able to apply advanced level control charts (CUSUM, EWMA) in a production process.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Measurement System Analysis-1 2 Measurement System Analysis-2 3 CUSUM Control Charts 4 EWMA Control Charts 5 Control Charts for short productions 6 Using design of experiments for product and process improvement 7 Experiments for one factor-1 8 Experiments for one factor-2 9 Full factorial designs with two levels-1 10 Full factorial designs with two levels-2 11 Fractional factorial designs with two levels 12 Blocking in fractional factorial designs with two levels 13 Taguchi loss function 14 Taguchi approach to design of experiments

Recomended or Required Reading

Introduction to Statistical Quality Control, D. Montgomery, John Wiley.

Planned Learning Activities and Teaching Methods

1) Class lecturing, 2) Lectures on applications, 3) Presentation 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 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

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)

kemal.sehirli@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 2 28 Preparations before/after weekly lectures 14 3 42 Preparation for midterm exam 1 10 10 Preparation for final exam 1 10 10 Preparing assignments 6 6 36 Midterm 1 2 2 Final 1 2 2 TOTAL WORKLOAD (hours) 130

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 LO.1 3 3 5 4 3 LO.2 3 3 5 4 3 LO.3 3 3 5 4 3 LO.4 3 5 4 3 LO.5 3 5 4 3