INDUSTRIAL ENGINEERING (ENGLISH, THESIS) | |||||
Master | TR-NQF-HE: Level 7 | QF-EHEA: Second Cycle | EQF-LLL: Level 7 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
INE5110 | Probabilistic Models and Applications | Fall | 3 | 0 | 3 | 8 |
The course opens with the approval of the Department at the beginning of each semester |
Language of instruction: | En |
Type of course: | Must Course |
Course Level: | |
Mode of Delivery: | Face to face |
Course Coordinator : | Dr. Öğr. Üyesi ETHEM ÇANAKOĞLU |
Course Lecturer(s): |
Dr. Öğr. Üyesi ETHEM ÇANAKOĞLU |
Course Objectives: | The objective of this course is to develop and extend the knowledge of mathematical techniques underlying the application of probability theory to well known engineering and operations research problems. This Ms level course is intended to cover stochastic models such as probability theory, random numbers, conditional probability, Markov processes, and Poisson processes. |
The students who have succeeded in this course; I. Identify the nature of probability models. II. Develop a model for a probabilistic real-life problem. III. Solve a constructed probabilistic model analytically. IV. Analyze stochastic processes in real-life. |
This course is offered in the Industrial Engineering master curriculum as a must course where the basic and fundamental knowledge of stochastic processes are given. After gaining knowledge of these topics, the students will be able to explore research and to do master theses related with both the theory and applications of the probabilistic models covered in this course. |
Week | Subject | Related Preparation | |
1) | Introduction | ||
2) | Random Variables | ||
3) | Jointly Distributed Random Variables | ||
4) | Conditional Probability | ||
5) | Conditional Conditional Expectation | ||
6) | Markov Chains | ||
7) | Limiting Probabilities of Markov Chains | ||
8) | Applications of Markov Chains | ||
9) | Midterm Exam | ||
10) | Exponential Distribution | ||
11) | Poisson Process | ||
12) | Markov Process | ||
13) | Limiting Probabilities of Markov Process | ||
14) | Queuing Theory | ||
15) | Final exam preparation | ||
16) | Final Exam |
Course Notes: | Introduction to Probability Models, 10th ed. Sheldon M. Ross. Academic Press, 2010 978-0-12-375686-2 |
References: | Stochastic Processes, 2nd ed. Sheldon M. Ross. Wiley, 1996 0-471-12062-6 |
Semester Requirements | Number of Activities | Level of Contribution |
Attendance | % 0 | |
Laboratory | % 0 | |
Application | % 0 | |
Field Work | % 0 | |
Special Course Internship (Work Placement) | % 0 | |
Quizzes | 2 | % 20 |
Homework Assignments | 5 | % 15 |
Presentation | % 0 | |
Project | % 0 | |
Seminar | % 0 | |
Midterms | 1 | % 25 |
Preliminary Jury | % 0 | |
Final | 1 | % 40 |
Paper Submission | % 0 | |
Jury | % 0 | |
Bütünleme | % 0 | |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 60 | |
PERCENTAGE OF FINAL WORK | % 40 | |
Total | % 100 |
Activities | Number of Activities | Workload | |
Course Hours | 13 | 37 | |
Laboratory | |||
Application | |||
Special Course Internship (Work Placement) | |||
Field Work | |||
Study Hours Out of Class | 15 | 104 | |
Presentations / Seminar | |||
Project | |||
Homework Assignments | 5 | 40 | |
Quizzes | 2 | 2 | |
Preliminary Jury | |||
Midterms | 1 | 3 | |
Paper Submission | |||
Jury | |||
Final | 1 | 3 | |
Total Workload | 189 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution | |
1) | Process view and analytic thinking | |
2) | managerial thinking with technical background | 3 |
3) | To have theoretical knowledge on operations research. | 5 |
4) | Awareness about the applications of operations research | 4 |
5) | To have ability of selection and efficient use of modern techniques, equipments and information technologies for industrial engineering | 3 |
6) | To be capable of designing and conducting experiments and collecting data, analyzing and interpreting results | 1 |
7) | To have verbal and oral effective communication skills by using visual methods in Turkish and English | |
8) | To be aware of entrepreneurship, sustainability and innovation | |
9) | To lead disciplinary and multi-disciplinary teams, to develop solution approaches in complex situations, to work individually and to take responsibility. | |
10) | To have conscious of professional and ethical responsibility | |
11) | To have conscious of necessity to lifelong learning | |
12) | To be aware of economic and legal implications of engineering solutions | |
13) | Economic, social and environmental responsibility while solving management problems |