Simulation

Course Code:

ISE 344

Course Period:

Spring

Course Type:

Core

Credits:

3

Theoric:

2

Practice:

0

Laboratory Hour:

2

ECTS:

5

Prerequisite Courses:

Operations Research II

Statistical Applications for Industrial Engineers

Course Language:

English

Courses given by:

Zeynep Gökçe İşlier

Course Objectives:

This course aims to provide an introduction to the fundamental methods used in systems simulation with particular emphasis on discrete event simulation.

Course Content:

Topics covered will include systems modeling using simulation, statistical models in simulation, random number and variate generation, input modeling, verification and validation, output analysis, and comparison of alternative designs. Course content will be supported by hands on experience with simulation software.

Course Methodology:

1: Lecture by instructor, 2: Lecture by instructor with class discussion, 3: Problem solving by instructor, 4: Use of simulations, 5: Problem solving assignment, 6: Reading assignment, 7: Laboratory work, 8: Term research paper

Course Evaluation Methods:

A: Written exam, B: Multiple-choice exam C: Quiz, D: Experiment report, E: Homework, F: Project, G: Presentation by student

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Course Learning Outcomes

Course Learning Outcomes	Detailed Program Outcomes	Teaching Methods	Assessment Methods
Defines areas of usage of simulation models and lists the differences between simulation and optimization models.	1a, 2a, 6c	1	A, C
Performs hand simulation.	2a, 2b, 6c	1, 3	A, C
Generates random numbers and random variates from different distributions.	1a, 1b, 6c	1, 3	A, C
Models simulation data using theoretical and empirical distributions.	2a, 2b, 6c	1, 3, 4, 7	A, C, F
Builds simulation models using ARENA.	2a, 2b, 3a, 3b, 4a, 4b	4, 7, 8	A, C, F
Verifies and validates simulation models.	3a, 3b, 5a, 5b, 6c,9a,9b	1, 3, 4	A, C, F
Analyzes the results of simulation models using statistical models.	1a, 1b, 5a, 5b, 6c	1, 3, 4, 7	A, C, F
Solves a real-life problem using simulation and teamwork; presents the results in oral and written form.	2a, 2b, 3a, 3b, 4a, 4b, 5a, 5b, 6a, 7b, 7c, 7d, 11b	1, 3, 4, 7, 8	F, G
Prepares written reports following the guidelines while meeting the deadlines	7a, 7e	8	F

Course Flow

COURSE CONTENT
Week	Topics	Study Materials
1	INTRODUCTION TO SIMULATION MODELING	Textbooks, Course Notes
2	FUNDAMENTAL SIMULATION CONCEPTS	Textbooks, Course Notes
3	STATISTICAL MODELS IN SIMULATION	Textbooks, Course Notes
4	QUEUEING MODELS	Textbooks, Course Notes
5	RANDOM NUMBER GENERATION	Textbooks, Course Notes
6	RANDOM NUMBER GENERATION	Textbooks, Course Notes
7	RANDOM VARIATE GENERATION	Textbooks, Course Notes
8	MIDTERM EXAM	Textbooks, Course Notes
9	INPUT MODELING, VERIFICATION OF SIMULATION MODELS	Textbooks, Course Notes
10	VALIDATION OF SIMULATION MODELS	Textbooks, Course Notes
11	OUTPUT ANALYSIS OF A TERMINATING SIMULATION MODEL	Textbooks, Course Notes
12	OUTPUT ANALYSIS OF A STEADY-STATE SIMULATION MODEL	Textbooks, Course Notes
13	COMPARISON OF ALTERNATIVE SYSTEM DESIGNS	Textbooks, Course Notes
14	TEAM PROJECT PRESENTATIONS	Textbooks, Course Notes

Recommended Sources

RECOMMENDED SOURCES
Textbook	Discrete-Event System Simulation, Jerry Banks, John Carson, Barry L. Nelson, David Nicol, 5th Ed., Prentice Hall, 2014. Simulation with ARENA, W. David Kelton, Randall P. Sadowski, David T. Sturrock, 6th Ed., McGraw-Hill, 2015.
Additional Resources	Simulation, Sheldon Ross, 5th Ed., Academic Press, 2013. Simulation Modeling and Analysis with ARENA, Tayfur Altiok, Benjamin Melamed, Academic Press, 2007.

Material Sharing

MATERIAL SHARING
Documents	PDF files of PowerPoint presentations
Assignments	Exercises from the textbook
Team Project	1 Project by teams of 4-5 students
Exams	1 Midterm, Quizzes and Final

Assessment

ASSESSMENT
IN-TERM STUDIES	NUMBER	PERCENTAGE
Midterm	1	25
Quizzes	4	20
Project	1	20
Total		65
CONTRIBUTION OF FINAL EXAMINATION TO OVERALL GRADE		35
CONTRIBUTION OF IN-TERM STUDIES TO OVERALL GRADE		65
Total		100

Course’s Contribution to Program

COURSE'S CONTRIBUTION TO PROGRAM OUTCOMES
No	Program Learning Outcomes	check X
1a	Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline,	X
1b	Ability to use theoretical and applied knowledge in these areas in complex engineering problems.	X
2a	Ability to identify, formulate, and solve complex engineering problems,	X
2b	Ability to select and apply proper analysis and modeling methods for this purpose.	X
3a	Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result,	X
3b	Ability to apply modern design methods for this purpose.	X
4a	Ability to devise, select and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice.	X
4b	Ability to employ information technologies effectively.	X
5a	Ability to design experiments for investigating complex engineering problems or discipline specific research questions,	X
5b	Ability to conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions.	X
6a	Ability to work efficiently in intra-disciplinary teams,	X
6b	Ability to work efficiently in multi-disciplinary teams,
6c	Ability to work individually.	X
7a	Ability to communicate effectively both orally and in writing,	X
7b	Knowledge of a minimum of one foreign language,	X
7c	Ability to write effective reports and comprehend written reports, prepare design and production reports,	X
7d	Ability to make effective presentations,	X
7e	Ability to give and receive clear and intelligible instructions.	X
8a	Recognition of the need for lifelong learning, ability to access information, ability to follow developments in science and technology,
8b	Ability to continue to educate him/herself.
9a	Consciousness to behave according to ethical principles and professional and ethical responsibility.	X
9b	Knowledge on standards used in engineering practice.	X
10a	Knowledge about business life practices such as project management, risk management, change management.
10b	Awareness in entrepreneurship and innovation.
10c	Knowledge about sustainable development.
11a	Knowledge about the global and social effects of engineering practices on health, environment, and safety,
11b	Knowledge about contemporary issues of the century reflected into the field of engineering.	X
11c	Awareness of the legal consequences of engineering solutions.

ECTS

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Course Duration	14	4	56
Hours for off-the-classroom study (Pre-study, practice)	14	2	28
Quizzes	4	1	4
Midterm examination	1	2	2
Project	1	35	35
Final Examination	1	2	2
Total Work Load			127
Total Work Load / 25 (h)			5.08
ECTS Credit of the Course			5

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