BACK

---

---

Course Unit Code	Course Unit Title	Type of Course Unit	Year of Study	Semester	Number of ECTS Credits
9101056052015	Response Surface Methods		1	1	8,00

---

Third Cycle

---

Language of Instruction

Turkish

---

Objectives of the Course

Response surface methodology, which is a method where statistical and mathematical techniques required for product and process development and optimization are used together, consists of experimental designs, modeling and optimization stages. In this context, it is aimed to equip students taking the course with experimental design, modeling and optimization skills.

---

Name of Lecturer(s)

---

Learning Outcomes

1	Be able to comprehend the design of experiment.
2	Be able to express lineer models for designed experiments.
3	Be able to have a general information about experiment design and data analysis.
4	Be able to create response surface models.
5	Be able to make analysis in the area of off-line quality control using response surface methodogoly .
6	Be able to use basic optimization techniques.

---

Mode of Delivery

Face to Face

---

Prerequisities and Co-Requisities

---

Recommended Optional Programme Components

[Yok]

---

Content of the Course

First order response surface model and designs: 2k factorial designs, fractional repetitions of 2k factorial designs, Simplex designs, Plackett-Burman designs Quadratic response surface model and designs: Orthogonal quadratic designs, Rotatable second order designs, 3k factorial designs, Box-Behnken design, Central-Composite design, cylindrically rotatable design Determination of optimum conditions: Analysis of first order prediction response surface model, steepest ascent method, analysis of second order prediction response surface model, determination of stationary point coordinates of response systems, canonical analysis, ridge analysis, Taguchi's durable parameter design, Dual response surface approach

---

Weekly Detailed Course Contents

Week	Subjects (Theoretical)	Teaching Methods	Preparatory
1	Introduction to response surface models
2	Matrix, least square approach, analysis of variance, basic information about design experiment
3	First order response surface models
4	First order response surface models
5	Second order response surface models
6	Second order response surface models
7	Second order response surface models
8	Second order response surface models
9	Midterm
10	Defining optimal settings
11	Defining optimal settings
12	Defining optimal settings
13	Defining optimal settings
14	Taguchi's robust parameter design
15	Dual response surface
16	Final

---

Text Book / Material / Recommended Resources

Response Surfaces Designs and Analysis, 1996, Khuri, A.I., Cornell, J.A., NewYork. Response Surface Methodology 3rd Edition, 2008, Myers, R.H., Montgomery, D.C., Anderson-Cook, C.M., Canada.

---

Planned Learning Activities and Teaching Methods

Activities are given in detail in the sections of "Assessment Methods and Criteria" and "Workload Calculation".

---

Assessment Methods and Criteria

Term (or Year) Learning Activities	Quantity	Weight
Midterm Examination	1	100
Total		100
End Of Term (or Year) Learning Activities	Quantity	Weight
Final Examination	1	100
Total		100
Term (or Year) Learning Activities		40
End Of Term (or Year) Learning Activities		60

---

Work Pacement(s)

---

Workload Calculation

Activities	Number	Time (hours)	Total Work Load (hours)
Midterm Examination	1	35	35
Final Examination	1	45	45
Attending Lectures	16	4	64
Individual Study for Homework Problems	4	1	4
Individual Study for Mid term Examination	1	35	35
Individual Study for Final Examination	1	45	45
Reading	16	1	16
Total Work Load (hours)			244

---

Contribution of Learning Outcomes to Programme Outcomes

	PO 1	PO 2	PO 3	PO 4	PO 5	PO 6	PO 7
LO 1	4			3
LO 2
LO 3
LO 4	4			5
LO 5					5
LO 6				4