COURSE UNIT TITLE

: ADVANCED STATISTICAL QUALITY CONTROL

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 5032 ADVANCED STATISTICAL QUALITY CONTROL ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR ALI RIZA FIRUZAN

Offered to

Statistics (English)
STATISTICS (ENGLISH)
Statistics (English)

Course Objective

This course is about the use of modern statistical methods for Quality Control and improvement. It provides comprehensive coverage of the subject from basic principles to state-of-the art concepts and applications. The objective is to give the student a sound understanding of the principles and the basis for applying them in a variety of situation

Learning Outcomes of the Course Unit

1   Describing fundamental elements of advanced statistical process-monitoring and control techniques
2   Understanding why applying several univariate control charts simultaneously to a set of related quality characteristics
3   Understanding how engineering process control transfers variability from the process output into a manipulatable variable
4   Understanding how designed experiments can be used to improve product design and improving process performance
5   Choosing the appropriate sampling plans and understanding the role of acceptance sampling in modern quality control systems

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Control Charts for Multiple-Stream Processes
2 Economic Design of Control Charts
3 The Multivariate EWMA Control Chart
4 Regression Adjustment, Assignment1
5 Process Monitoring and Process Regulation
6 Process Control by Feedback Adjustment
7 Guidelines for Designing Experiments, Factorial Experiments
8 Midterm
9 Fractional Replication of the 2^k Design, Assignment2
10 Response Surface Methods and Designs
11 The Dodge- Roming Sampling Plans
12 Double, Multiple,and Sequential Sampling
13 Designing a Variables Sampling Plan with a Specified OC Curve, Presentation
14 Other Variables Sampling Procedures

Recomended or Required Reading

Douglas C. Montgomery, Introduction to Statistical Quality Control, 6th Edition, John Wiley and Sons, New York, 2009

Planned Learning Activities and Teaching Methods

Lecture, Homeworks, Presentation

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 PRS PRESENTATION
4 FIN FINAL EXAM
5 FCG FINAL COURSE GRADE MTE* 0.30 + ASG * 0.20 + PRS * 0.10 + FIN * 0.40
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) MTE* 0.30 + ASG * 0.20 + PRS * 0.10 + RST * 0.40


Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of homework assignments and examinations, presentation.

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: aliriza.firuzan@deu.edu.tr
Tel: 0232 301 85 55

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparation before/after weekly lectures 14 2 28
Preparing Individual Assignments 2 15 30
Preparing Presentations 1 15 15
Preparation for Mid-term Exam 1 35 35
Preparation for Final Exam 1 45 45
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 199

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.15555
LO.2545554
LO.3555555
LO.44555544
LO.55555555