Simulation (IE 305)

2025 Fall
Faculty of Engineering and Natural Sciences
Industrial Engineering(IE)
3
6
Murat Fadıloğlu murat.fadiloglu@sabanciuniv.edu,
Click here to view.
English
Undergraduate
MATH306
Formal lecture,Recitation
Interactive,Learner centered,Discussion based learning,Project based learning,Simulation
Click here to view.

CONTENT

Simulation Modeling and analysis of manufacturing and service systems; simulation modeling perspectives; discrete event simulation; simulation languages/ software; statistical aspects of simulation.

OBJECTIVE

By the end of this course, successful students should have learnt the principles of simulation, modelling, and statistical analysis for discrete event systems as well as the techniques and tools to apply those principles on a computer, in particular using the simulation software package ARENA.

LEARNING OUTCOMES

  • Describe the principles of simulation modeling and analysis for discrete event systems
  • Identify probability distributions and perform statistical analysis of both input and output data
  • Construct the computer-based simulation model for a given discrete event system

PROGRAMME OUTCOMES


1. Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others. 2

2. Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice. 2

3. Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects; have the ability to continue to educate him/herself. 5

4. Communicate effectively in Turkish and English by oral, written, graphical and technological means. 4

5. Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams. 4


1. Possess sufficient knowledge of mathematics, science, fundamental engineering, computational methods and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems. 4

2. Identify, define, formulate and solve complex engineering problems while considering the UN Sustainable Development Goals; choose and apply suitable analysis, design, estimation/prediction and modeling methods for this purpose. 5

3. Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; use information technologies effectively. 4

4. Have the ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling creative current and future requirements. 4

5. Use research methods, including conducting literature reviews, designing experiments, performing experiments, collecting data, analyzing results, and interpreting results, to investigate complex engineering problems or discipline-specific research topics. 4

6. Possess knowledge of business practices such as project management, risk management, change management, and economic feasibility analysis; awareness on entrepreneurship and innovation. 3

7. Possess knowledge of impact of engineering solutions on society, health and safety, the economy, sustainability, and the environment within the framework of the UN Sustainable Development Goals; awareness on legal outcomes of engineering solutions; awareness of acting impartially and inclusively without any form of discrimination; act in accordance with ethical principles, possessing knowledge of professional and ethical responsibilities. 3

8. Communicate effectively, both orally and in writing, on technical subjects, considering the diverse characteristics of the target audience (such as education, language, and profession). 4

ASSESSMENT METHODS and CRITERIA

  Percentage (%)
Final 40
Midterm 30
Participation 20
Group Project 10

RECOMENDED or REQUIRED READINGS

Textbook

Simulation With Arena, W. David Kelton, Randall P. Sadowski, and David
T. Sturrock, McGraw-Hill.

Discrete-event System Simulation, Jerry Banks, John Carson, Barry L.
Nelson, and David Nicol, Prentice Hall.

SUCourse: Lecture notes, recitation notes, Arena examples, past exams, announcements, etc.