INE6150 Design of ExperimentsBahçeşehir UniversityDegree Programs INDUSTRIAL ENGINEERING (ENGLISH, THESIS)General Information For StudentsDiploma SupplementErasmus Policy StatementNational Qualifications
INDUSTRIAL ENGINEERING (ENGLISH, THESIS)
Master TR-NQF-HE: Level 7 QF-EHEA: Second Cycle EQF-LLL: Level 7

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
INE6150 Design of Experiments Fall 3 0 3 8
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: English
Type of course: Departmental Elective
Course Level:
Mode of Delivery: Face to face
Course Coordinator :
Recommended Optional Program Components: N.A.
Course Objectives: The aim of the course is to introduce the most commonly used experiments in engineering studies, to discuss the ideas, principles and assumptions required for the construction, implementation, and validity of the analysis for each experimental design and to analyze the resulting data. Applications with statistical software packages are also utilized.

Learning Outcomes

The students who have succeeded in this course;
I. Explain the difference between fixed and random factors.
II. Recognize the difference between completely randomized design and randomized blocks.
III. Design and conduct experiments involving several factors using the factorial design approach.
IV. Use ANOVA to analyze the data from the experiments.
V. Analyze and interpret main effects and interactions.
VI. Design and conduct experiments involving the randomized complete block design.
VII. Design and conduct fractional factorial designs.
VIII. Assess model adequacy with residual analyses.
IX. Perform power analysis and calculate the sample size required for a design.

Course Content

Randomization, replication, blocking, transformations, fixed and random effect models, single factor experiments (analysis of variance), Latin squares, factorial designs, fractional factorial designs.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Introduction to Designed Experiments
2) Basic Statistical Methods
3) Basic Statistical Methods
4) Analysis of Variance
6) Analysis of Variance
7) Experiments with Blocking Factors
8) Experiments with Blocking Factors
9) Midterm Exam
10) Factorial Experiments
11) Factorial Experiments
12) Two-Level Fractional Factorial Designs
13) Two-Level Fractional Factorial Designs
14) Project presentations

Sources

Course Notes / Textbooks: Douglas C. Montgomery, 2012. Design and Analysis of Experiments, John Wiley & Sons, 8th Edition
References: N.A.

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Homework Assignments 4 % 10
Project 1 % 20
Midterms 1 % 30
Final 1 % 40
Total % 100
PERCENTAGE OF SEMESTER WORK % 40
PERCENTAGE OF FINAL WORK % 60
Total % 100

ECTS / Workload Table

Activities Number of Activities Workload
Course Hours 14 42
Study Hours Out of Class 14 28
Presentations / Seminar 1 10
Project 4 40
Homework Assignments 4 40
Midterms 1 15
Final 1 20
Total Workload 195

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Process view and analytic thinking 1
2) managerial thinking with technical background 3
3) To have theoretical knowledge on operations research.
4) Awareness about the applications of operations research
5) To have ability of selection and efficient use of modern techniques, equipments and information technologies for industrial engineering 4
6) To be capable of designing and conducting experiments and collecting data, analyzing and interpreting results 5
7) To have verbal and oral effective communication skills by using visual methods in Turkish and English
8) To be aware of entrepreneurship, sustainability and innovation
9) To lead disciplinary and multi-disciplinary teams, to develop solution approaches in complex situations, to work individually and to take responsibility. 1
10) To have conscious of professional and ethical responsibility
11) To have conscious of necessity to lifelong learning
12) To be aware of economic and legal implications of engineering solutions
13) Economic, social and environmental responsibility while solving management problems