COURSE UNIT TITLE

: STATISTICAL PROCESS DESIGN AND IMPROVEMENT

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 5095 STATISTICAL PROCESS DESIGN AND IMPROVEMENT ELECTIVE 3 0 0 7

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSISTANT PROFESSOR SENEM VAHAPLAR

Offered to

Statistics
Statistics
STATISTICS

Course Objective

The objective of this course is to cover an advanced level of Statistical Process Design and Industrial Process Improvement via Statistical Design of Experiments.

Learning Outcomes of the Course Unit

1   Understanding basic elements of experimental design
2   Constituting factorial experiments
3   Constituting 2^k factorial experiments
4   Being capable of applications of response surface methods
5   Synthesizing process robustness studies

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 What is Experimental Design
2 Basic Principles and Guidelines of Experimental Design
3 Factorial Experiments (1), Assignment 1
4 Factorial Experiments (2)
5 2^k Factorial Experiments (1)
6 2^k Factorial Experiments (2)
7 Process Optimization with Designed Experiments, Response Surfaces
8 Midterm Exam
9 The Method of Steepest Ascent
10 Process Robustness Studies, Assignment 2
11 Robust Parameter Design Problem
12 Taguchi Loss Functions and Experimental Methods
13 Applications of Factorial Experiment
14 Applications of Response Surface Methods and Robustness Studies

Recomended or Required Reading

D. C. Montgomery, Design and Analysis of Experiments, 3rd ed., Wiley, 2001.

Planned Learning Activities and Teaching Methods

Lecture, presentation, homework assignment.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE * 0.30 +ASG * 0.20 +FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + ASG * 0.20 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of homework assignments and examinations.

Language of Instruction

English

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at http://web.deu.edu.tr/fen.

Contact Details for the Lecturer(s)

DEU Fen Fakültesi Istatistik Bölümü
e-mail: senem.sahan@deu.edu.tr
Tel: 0232 301 86 03

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 2 28
Preparation for midterm exam 1 24 24
Preparation for final exam 1 36 36
Preparing individual assignments 4 12 48
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 182

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.1555
LO.2555
LO.3555
LO.4555
LO.5555

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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