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  Course Description
Course Name : Stochastic Processes

Course Code : EM-550

Course Type : Optional

Level of Course : Second Cycle

Year of Study : 1

Course Semester : Spring (16 Weeks)

ECTS : 6

Name of Lecturer(s) : Instructor MELİK KOYUNCU

Learning Outcomes of the Course : Gains the knowledge about basic statistical concepts
Gains the knowledge about Markov processes
Gains the knowledge about queing systems
Analyzes some operations systems by queuing theory
Gains the knowledge about queing networks

Mode of Delivery : Face-to-Face

Prerequisites and Co-Prerequisites : None

Recommended Optional Programme Components : None

Aim(s) of Course : This course aims to analyze the modern operations systems using basic statistical concepts, Markov processes and queing theory knowledge.

Course Contents : Basic terms and concepts, Descriptive and Inferential Statistics, Continuous distributions, Introductipn to Markov processes, one-step transition matrix and analyzing steady state probabilities, Implementation of Markov process, M/M1queing models, non-exponential queing models, queing networks.

Language of Instruction : Turkish

Work Place : Class room


  Course Outline /Schedule (Weekly) Planned Learning Activities
Week Subject Student's Preliminary Work Learning Activities and Teaching Methods
1 Basic statistical concepts Reading the related chapter from text books Power point presentation and explanation on board
2 Descriptive and Inferential statistics Reading the related chapter from text books Power point presentation and explanation on board
3 Discrete distributions Reading the related chapter from text books Power point presentation and explanation on board
4 Continious distributions Reading the related chapter from text books Power point presentation and explanation on board
5 Introduction to Markov Processes Reading the related chapter from text books Power point presentation and explanation on board
6 Calculation of one step transition matrix and steady state prpbabilities Reading the related chapter from text books Power point presentation and explanation on board
7 Midterm exam Written exam
8 Application area of Markov processes Reading the related chapter from text books Power point presentation and explanation on board
9 Introduction to queuing theory Reading the related chapter from text books Power point presentation and explanation on board
10 Birth and Death Process Reading the related chapter from text books Power point presentation and explanation on board
11 M/M/1 queuing systems Reading the related chapter from text books Power point presentation and explanation on board
12 M/M/s queuing systems Reading the related chapter from text books Power point presentation and explanation on board
13 Non exponential queuing systems Reading the related chapter from text books Power point presentation and explanation on board
14 Queuing networks Reading the related chapter from text books Power point presentation and explanation on board
15 Project presentation Studying presenatation Student presentation
16/17 Final exam Written exam


  Required Course Resources
Resource Type Resource Name
Recommended Course Material(s)  
 
Required Course Material(s)


  Assessment Methods and Assessment Criteria
Semester/Year Assessments Number Contribution Percentage
    Mid-term Exams (Written, Oral, etc.) 1 90
    Homeworks/Projects/Others 1 10
Total 100
Rate of Semester/Year Assessments to Success 40
 
Final Assessments 100
Rate of Final Assessments to Success 60
Total 100

  Contribution of the Course to Key Learning Outcomes
# Key Learning Outcome Contribution*
1 Understand, interpret and apply knowledge in his/her field domain both in-depth and in-breadth by doing scientific research in industrial engineering. 5
2 Acquire comprehensive knowledge about methods and tools of industrial engineering and their limitations. 4
3 Work in multi-disciplinary teams and take a leading role and responsibility. 4
4 Identify, gather and use necessary information and data. 4
5 Complete and apply the knowledge by using scarce and limited resources in a scientific way and integrate the knowledge into various disciplines. 4
6 Keep up with the recent changes and applications in the field of Industrial Engineering and analyze these innovations when necessary. 4
7 Work in multi-disciplinary teams, take a leading role and responsibility and develop solutions for complex problems. 5
8 Analyze Industrial Engineering problems, develop innovative methods to solve the problems. 5
9 Have the ability to propose new and/or original ideas and methods in developing innovative solutions for designing systems, components or processes. 3
10 Design and perform analytical modeling and experimental research and analyze/solve complex matters emerged in this process. 5
11 Follow, study and learn new and developing applications of industrial engineering. 4
12 Use a foreign language in verbal and written communication at least B2 level of European Language Portfolio. 4
13 Present his/her research findings systematically and clearly in oral and written forms in national and international platforms. 4
14 Understand social and environmental implications of engineering practice. 2
15 Consider social, scientific and ethical values in the process of data collection, interpretation and announcement of the findings. 5
* Contribution levels are between 0 (not) and 5 (maximum).

  Student Workload - ECTS
Works Number Time (Hour) Total Workload (Hour)
Course Related Works
    Class Time (Exam weeks are excluded) 14 3 42
    Out of Class Study (Preliminary Work, Practice) 14 6 84
Assesment Related Works
    Homeworks, Projects, Others 1 10 10
    Mid-term Exams (Written, Oral, etc.) 1 1 1
    Final Exam 1 2 2
Total Workload: 139
Total Workload / 25 (h): 5.56
ECTS Credit: 6