GRADUATE SCHOOL

M.SC. In Industrial Engineering (With Thesis)

STAT 554 | Course Introduction and Application Information

Course Name
Statistical Process Control
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
STAT 554
Fall/Spring
3
0
3
7.5

Prerequisites
None
Course Language
English
Course Type
Elective
Course Level
Second Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course -
Course Coordinator -
Course Lecturer(s)
Assistant(s) -
Course Objectives This course aims to improve the knowledge of students about control on statıstical processes in production and service systems.
Learning Outcomes The students who succeeded in this course;
  • will be able to propose control methods for stochastics processes.
  • will be able to prepare control charts for statistical processes.
  • will be able to apply SPC methods in stochastic systems.
  • will be able to apply SPC methods for solving engineering problems.
  • will be able to propose control systems.
  • will be able to define the stochastic processes.
Course Description Basic topics of this course are: Basics of statistics, Quality control systems,methods of stochastics processes.

 



Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Statistical methods and definition of control “Introduction to Statistical Quality Control” by D. C. Montgomery, Wiley, 4th edition 2000. ISBN-13: 978-0471316480
2 Quality of modelling process “Introduction to Statistical Quality Control” by D. C. Montgomery, Wiley, 4th edition 2000. ISBN-13: 978-0471316480
3 Inference for process quality “Introduction to Statistical Quality Control” by D. C. Montgomery, Wiley, 4th edition 2000. ISBN-13: 978-0471316480
4 Statistical process control and methods for analysis “Introduction to Statistical Quality Control” by D. C. Montgomery, Wiley, 4th edition 2000. ISBN-13: 978-0471316480
5 Control charts for process variables “Introduction to Statistical Quality Control” by D. C. Montgomery, Wiley, 4th edition 2000. ISBN-13: 978-0471316480
6 Control charts for process identifications “Introduction to Statistical Quality Control” by D. C. Montgomery, Wiley, 4th edition 2000. ISBN-13: 978-0471316480
7 Process and Measurement analysis “Introduction to Statistical Quality Control” by D. C. Montgomery, Wiley, 4th edition 2000. ISBN-13: 978-0471316480
8 Cumulative sum and exponentially weighted moving average control charts “Introduction to Statistical Quality Control” by D. C. Montgomery, Wiley, 4th edition 2000. ISBN-13: 978-0471316480
9 Univariate statistical process monitoring and control techniques “Introduction to Statistical Quality Control” by D. C. Montgomery, Wiley, 4th edition 2000. ISBN-13: 978-0471316480
10 Multivariate process monitoring and control “Introduction to Statistical Quality Control” by D. C. Montgomery, Wiley, 4th edition 2000. ISBN-13: 978-0471316480
11 Engineering process control and SPC “Introduction to Statistical Quality Control” by D. C. Montgomery, Wiley, 4th edition 2000. ISBN-13: 978-0471316480
12 Factorial and fractional factorial experiments for process design and improvement “Introduction to Statistical Quality Control” by D. C. Montgomery, Wiley, 4th edition 2000. ISBN-13: 978-0471316480
13 Process optimization with designed experiments “Introduction to Statistical Quality Control” by D. C. Montgomery, Wiley, 4th edition 2000. ISBN-13: 978-0471316480
14 Acceptance sampling “Introduction to Statistical Quality Control” by D. C. Montgomery, Wiley, 4th edition 2000. ISBN-13: 978-0471316480
15 Semester review
16 Final exam

 

Course Notes/Textbooks

“Introduction to Statistical Quality Control” by D. C. Montgomery, Wiley, 4th edition 2000. ISBN-13: 978-0471316480

Suggested Readings/Materials

“Statistical Decision Theory and Bayesian Analysis” by James O. Berger, Springer.2nd edition,1985. ISBN-13: 978-0387960982

“Applied Statistical Decision Theory” by H. Raiffa and R. Schlaifer. Wiley-Interscience; 1st edition,2000. ISBN-13: 978-0471383499

“Statistical Inference” by George Casella and Roger L. Berger. Cengage Learning; 2nd edition,2001. ISBN-13: 978-0534243128

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project
1
20
Seminar / Workshop
Oral Exams
Midterm
1
30
Final Exam
1
50
Total

Weighting of Semester Activities on the Final Grade
50
Weighting of End-of-Semester Activities on the Final Grade
50
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
0
Study Hours Out of Class
14
6
84
Field Work
0
Quizzes / Studio Critiques
0
Portfolio
0
Homework / Assignments
0
Presentation / Jury
0
Project
1
20
20
Seminar / Workshop
0
Oral Exam
0
Midterms
1
33
33
Final Exam
1
40
40
    Total
225

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To have an appropriate knowledge of methodological and practical elements of the basic sciences and to be able to apply this knowledge in order to describe engineering-related problems in the context of industrial systems.

2

To be able to identify, formulate and solve Industrial Engineering-related problems by using state-of-the-art methods, techniques and equipment.

3

To be able to use techniques and tools for analyzing and designing industrial systems with a commitment to quality.

4

To be able to conduct basic research and write and publish articles in related conferences and journals.

5

To be able to carry out tests to measure the performance of industrial systems, analyze and interpret the subsequent results.

6

To be able to manage decision-making processes in industrial systems.

7

To have an aptitude for life-long learning; to be aware of new and upcoming applications in the field and to be able to learn them whenever necessary.

8

To have the scientific and ethical values within the society in the collection, interpretation, dissemination, containment and use of the necessary technologies related to Industrial Engineering.

9

To be able to design and implement studies based on theory, experiments and modeling; to be able to analyze and resolve the complex problems that arise in this process; to be able to prepare an original thesis that comply with Industrial Engineering criteria.

10

To be able to follow information about Industrial Engineering in a foreign language; to be able to present the process and the results of his/her studies in national and international venues systematically, clearly and in written or oral form.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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