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IE 403
Quality Planning and Control

Faculty Faculty of Engineering and Natural Sciences
Semester Spring 2025-2026
Course IE 403 - Quality Planning and Control
Time/Place
Time
Week Day
Place
Date
09:40-11:30
Tue
FASS-1050
Feb 16-May 22, 2026
14:40-15:30
Thu
FASS-1050
Feb 16-May 22, 2026
Level of course Undergraduate
Course Credits SU Credit:3, ECTS:6, Engineering:6
Prerequisites MATH 306
Corequisites
Course Type Lecture

Instructor(s) Information

Semih Onur Sezer

Course Information

Catalog Course Description
Introduction to total quality management philosophies and ISO 9000 standards; design and analysis of statistical process control systems; Six Sigma problem solving tools; acceptance sampling techniques; reliability testing; evaluation of the source of variation; design of experiments; failure modes & effects analysis; quality by design and introduction to Taguchi approach.
Course Learning Outcomes:
1. Define product and process quality; identify inefficiencies within manufacturing or service operations using Lean Six Sigma tools
2. Collect and visualize data on process parameters, inputs and outputs after validating measurement systems in order to assess process capability
3. Identify root causes of process inefficiencies using statistical analysis such as Hypothesis Testing or Multiple Regression
4. Develop and test process improvement solutions with Failure Mode and Effects Analysis (FMEA)
5. Generate statistical process control (SPC) plans with appropriate SPC tools or acceptance sampling strategies
Course Objective
Course objectives (and program outcomes):
This course aims to equip students with the necessary statistical methods and problem solving techniques to improve product and service quality. By the completion of the course, the students will be able to;

• Define product and process quality; identify inefficiencies within manufacturing or service operations using Lean Six Sigma tools

• Collect and visualize data on process parameters, inputs and outputs after validating measurement systems in order to assess process capability

• Identify root causes of process inefficiencies using statistical analysis such as Hypothesis Testing or Multiple Regression

• Develop and test process improvement solutions with Failure Mode and Effects Analysis (FMEA)

• Generate statistical process control (SPC) plans with appropriate SPC tools or acceptance sampling strategies
Sustainable Development Goals (SDGs) Related to This Course:
Decent Work and Economic Growth
Industry, Innovation and Infrastructure

Course Materials

Resources:
See the syllabus file
Technology Requirements:

Policies