Industrial Engineering (English) Preview
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

General course introduction information

Course Code:

IE433

Course Name:

Special Topics in Industrial Engineering II

Course Semester:

Fall

Course Credits:

Theoretical	Practical	Credit	ECTS
3	0	3	5

Language of instruction:

Course Requisites:

Does the Course Require Work Experience?:

Type of course:

Compulsory

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Dr.Öğr.Üyesi AHMET UMUR ÖZSOY

Course Lecturer(s):

Course Assistants:

Course Objective and Content

Course Objectives:

This course provides a rigorous yet intuitive introduction to Markov chains and stochastic processes. Students learn to model, analyze, and simulate systems that evolve randomly over time, focusing on discrete-time and continuous-time Markov chains, state classification, long-run behavior, and applications in finance, operations, and engineering. Emphasis is placed on both theoretical foundations (transition matrices, steady-state distributions, absorption, and reversibility) and practical modeling through real-life examples such as queueing, reliability, and investment processes

Course Content:

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Define and classify stochastic processes and explain the Markov property.
2) Construct transition matrices and use them to compute multi-step probabilities.
3) Model real-life systems (e.g., queueing, reliability, credit risk) as discrete- or continuous-time Markov chains.
4) Communicate technical results clearly, both in written reports and oral presentations
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Lesson Plan

Week	Subject	Related Preparation
1)	Introduction to Stochastic Processes
2)	Definition of Markov chains
3)	Transition porbability matrices
4)	First Passage Times and Hitting Probabilities
5)	First Passage Times and Hitting Probabilities
6)	First Passage Times and Hitting Probabilities
7)	First Passage Times and Hitting Probabilities
8)	Steady-State and Limiting Distributions
9)	Analytical and computational problems
10)	Continuous-Time Markov Chains (CTMCs)
11)	Continuous-Time Markov Chains (CTMCs)
12)	Birth-Death Processes
13)	Project Presentations
14)	Project Presentations

Sources

Course Notes / Textbooks:
References:

Course-Program Learning Outcome Relationship

Learning Outcomes	1	2	3	4
Program Outcomes
1) A solid foundation in mathematics, natural sciences, and industrial engineering; the ability to apply both theoretical and practical knowledge in these fields to model and solve complex engineering problems.
2) The ability to identify, define, formulate, and solve complex industrial engineering problems; and to select and apply appropriate analysis and modeling methods for this purpose.
3) The ability to design complex industrial engineering systems, processes, devices, or products to meet specified requirements under realistic constraints and conditions; and to apply modern design methodologies for this purpose. (Realistic constraints and conditions may include economic, environmental, sustainability, manufacturability, ethical, health, safety, social, and political factors depending on the nature of the design.)
4) The ability to develop, select, and use modern techniques and tools required for the analysis and solution of complex problems encountered in industrial engineering applications such as production, quality, finance, and ergonomics; and the ability to effectively utilize information technologies.
5) The ability to design and conduct experiments, collect data, analyze and interpret results for the investigation of complex problems in industrial engineering areas such as production planning, quality, finance, and ergonomics.
6) The ability to work effectively both individually and in disciplinary and multidisciplinary teams (particularly with computer and mechanical engineering).
7) The ability to communicate effectively in both Turkish and English, both orally and in writing; including effective report writing and comprehension of written reports, preparation of reports, delivering effective presentations, and the ability to give and receive clear and understandable instructions.
8) Awareness of the necessity of lifelong learning required by industrial engineering; the ability to access, interpret, and develop knowledge, to follow advancements in science and technology, and to continuously update oneself.
9) The ability to act in accordance with ethical principles; awareness of professional and ethical responsibilities, and knowledge of standards used in industrial engineering practices.
10) Knowledge of project management and industrial engineering practices such as risk management and change management; awareness of entrepreneurship, innovation, and sustainable development.
11) Knowledge of the impacts of industrial engineering applications on health, environment, and safety at universal and societal levels; awareness of contemporary issues and the legal implications of engineering solutions.

Course - Learning Outcome Relationship

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	A solid foundation in mathematics, natural sciences, and industrial engineering; the ability to apply both theoretical and practical knowledge in these fields to model and solve complex engineering problems.	5
2)	The ability to identify, define, formulate, and solve complex industrial engineering problems; and to select and apply appropriate analysis and modeling methods for this purpose.	5
3)	The ability to design complex industrial engineering systems, processes, devices, or products to meet specified requirements under realistic constraints and conditions; and to apply modern design methodologies for this purpose. (Realistic constraints and conditions may include economic, environmental, sustainability, manufacturability, ethical, health, safety, social, and political factors depending on the nature of the design.)
4)	The ability to develop, select, and use modern techniques and tools required for the analysis and solution of complex problems encountered in industrial engineering applications such as production, quality, finance, and ergonomics; and the ability to effectively utilize information technologies.
5)	The ability to design and conduct experiments, collect data, analyze and interpret results for the investigation of complex problems in industrial engineering areas such as production planning, quality, finance, and ergonomics.
6)	The ability to work effectively both individually and in disciplinary and multidisciplinary teams (particularly with computer and mechanical engineering).
7)	The ability to communicate effectively in both Turkish and English, both orally and in writing; including effective report writing and comprehension of written reports, preparation of reports, delivering effective presentations, and the ability to give and receive clear and understandable instructions.	5
8)	Awareness of the necessity of lifelong learning required by industrial engineering; the ability to access, interpret, and develop knowledge, to follow advancements in science and technology, and to continuously update oneself.
9)	The ability to act in accordance with ethical principles; awareness of professional and ethical responsibilities, and knowledge of standards used in industrial engineering practices.
10)	Knowledge of project management and industrial engineering practices such as risk management and change management; awareness of entrepreneurship, innovation, and sustainable development.
11)	Knowledge of the impacts of industrial engineering applications on health, environment, and safety at universal and societal levels; awareness of contemporary issues and the legal implications of engineering solutions.

Learning Activity and Teaching Methods

Assessment & Grading Methods and Criteria

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
total		%
PERCENTAGE OF SEMESTER WORK		% 0
PERCENTAGE OF FINAL WORK		%
total		%