GRADUATE SCHOOL
M.SC. In Industrial Engineering (With Thesis)
IE 540 | Course Introduction and Application Information
| Course Name |
Applied Stochastic Processes
|
|
Code
|
Semester
|
Theory
(hour/week) |
Application/Lab
(hour/week) |
Local Credits
|
ECTS
|
|
IE 540
|
Fall/Spring
|
3
|
0
|
3
|
7.5
|
| Prerequisites |
None
|
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| Course Language |
English
|
|||||
| Course Type |
Elective
|
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| Course Level |
Second Cycle
|
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| Mode of Delivery | - | |||||
| Teaching Methods and Techniques of the Course | - | |||||
| Course Coordinator | - | |||||
| Course Lecturer(s) | - | |||||
| Assistant(s) | - | |||||
| Course Objectives | The emphasis of the course will be on the development of tools that are useful in the analysis of stochastic systems that appear in real life. The course will start with the introduction to probability theory, distributions, and expectations and then continue with poisson process and Markov chains. The renewal theory, queueing theory and realibity theory based on the based on stochastic processes. |
| Learning Outcomes |
The students who succeeded in this course;
|
| Course Description | Topics of this course include the probability theory, conditional probability and expectation, Exponential distribution, Poisson process, Markov Chains, renewal theory, queueing theory, and realibility theory. |
|
|
Core Courses | |
| Major Area Courses |
X
|
|
| Supportive Courses | ||
| Media and Management Skills Courses | ||
| Transferable Skill Courses |
WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES
| Week | Subjects | Related Preparation |
| 1 | Introduction to Probability Theory | Textbook Chapter 1 |
| 2 | Random Variables | Textbook Chapter 2 |
| 3 | Conditional Probability and Conditional Expectation | Textbook Chapter 3 |
| 4 | Markov Chains | Textbook Chapter 4 |
| 5 | Exponential Distribution and the Poisson Process | Textbook Chapter 5 |
| 6 | Exponential Distribution and the Poisson Process | Textbook Chapter 5 |
| 7 | Midterm | |
| 8 | Continuous-Time Markov Chains | Textbook Chapter 6 |
| 9 | Continuous-Time Markov Chains | Textbook Chapter 6 |
| 10 | Renewal Theory | Textbook Chapter 7 |
| 11 | Renewal Theory | Textbook Chapter 7 |
| 12 | Queueing Theory | Textbook Chapter 8 |
| 13 | Queueing Theory | Textbook Chapter 8 |
| 14 | Reliability Theory | Textbook Chapter 9 |
| 15 | Reliability Theory | Textbook Chapter 9 |
| 16 | Review of the Semester |
| Course Notes/Textbooks | Sheldon M. Ross, Introduction to Probability Models, Academic Press. Instructor notes and lecture slides. |
| Suggested Readings/Materials |
EVALUATION SYSTEM
| Semester Activities | Number | Weigthing |
| Participation | ||
| Laboratory / Application | ||
| Field Work | ||
| Quizzes / Studio Critiques | ||
| Portfolio | ||
| Homework / Assignments |
4
|
40
|
| Presentation / Jury | ||
| Project | ||
| Seminar / Workshop | ||
| Oral Exams | ||
| Midterm |
1
|
30
|
| Final Exam |
1
|
30
|
| Total |
| Weighting of Semester Activities on the Final Grade |
60
|
|
| Weighting of End-of-Semester Activities on the Final Grade |
40
|
|
| 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 |
15
|
6
|
90
|
| Field Work |
0
|
||
| Quizzes / Studio Critiques |
10
|
0
|
|
| Portfolio |
0
|
||
| Homework / Assignments |
0
|
||
| Presentation / Jury |
0
|
||
| Project |
0
|
||
| Seminar / Workshop |
0
|
||
| Oral Exam |
0
|
||
| Midterms |
1
|
20
|
20
|
| Final Exam |
1
|
27
|
27
|
| Total |
185
|
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. |
X | ||||
| 2 | To be able to identify, formulate and solve Industrial Engineering-related problems by using state-of-the-art methods, techniques and equipment. |
X | ||||
| 3 | To be able to use techniques and tools for analyzing and designing industrial systems with a commitment to quality. |
X | ||||
| 4 | To be able to conduct basic research and write and publish articles in related conferences and journals. |
X | ||||
| 5 | To be able to carry out tests to measure the performance of industrial systems, analyze and interpret the subsequent results. |
X | ||||
| 6 | To be able to manage decision-making processes in industrial systems. |
X | ||||
| 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. |
X | ||||
| 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. |
X | ||||
| 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. |
X | ||||
| 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. |
X | ||||
*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest