Code IE 305
Term 201603
Title Simulation
Faculty Faculty of Engineering and Natural Sciences
Subject Industrial Engineering(IE)
SU Credit 3
ECTS Credit 6.00 / 6.00 ECTS (for students admitted in the 2013-14 Academic Year or following years)
Instructor(s) Sinan Y?ld?r?m sinanyildirim@sabanciuniv.edu,
Detailed Syllabus
Language of Instruction English
Prerequisites
(only for SU students)
MATH306
Mode of Delivery Formal lecture,Recitation
Planned Learning Activities Learner centered,Discussion based learning,Project based learning,Simulation
Content

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

Objective

By the end of this course, successful students should have learnt the principles of simulation, modeling, 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 Outcome

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 simulation model of a given system using the simulation software package ARENA

Programme Outcomes

 Common Outcomes For All Programs 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. 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 Common Outcomes ForFaculty of Eng. & Natural Sci. 1 Possess sufficient knowledge of mathematics, science 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; choose and apply suitable analysis 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; possess knowledge of standards used in engineering applications; use information technologies effectively. 4 4 Ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling specified needs; apply modern design techniques for this purpose. 4 5 Design and conduct experiments, collect data, analyze and interpret the results to investigate complex engineering problems or program-specific research areas. 4 6 Knowledge of business practices such as project management, risk management and change management; awareness on innovation; knowledge of sustainable development. 3 7 Knowledge of impact of engineering solutions in a global, economic, environmental, health and societal context; knowledge of contemporary issues; awareness on legal outcomes of engineering solutions; understanding of professional and ethical responsibility. 3 Industrial Engineering Program Outcomes Required Courses 1 Formulate and analyze problems in complex manufacturing and service systems by comprehending and applying the basic tools of industrial engineering such as modeling and optimization, stochastics, statistics. 5 2 Design and develop appropriate analytical solution strategies for problems in integrated production and service systems involving human capital, materials, information, equipment, and energy. 3 3 Implement solution strategies on a computer platform for decision-support purposes by employing effective computational and experimental tools. 4 Molecular Biology, Genetics and Bioengineering Program Outcomes Area Electives 1 Comprehend key concepts in biology and physiology, with emphasis on molecular genetics, biochemistry and molecular and cell biology as well as advanced mathematics and statistics. 1 2 Develop conceptual background for interfacing of biology with engineering for a professional awareness of contemporary biological research questions and the experimental and theoretical methods used to address them. 1 Materials Science and Nano Engineering Program Outcomes Area Electives 1 Applying fundamental and advanced knowledge of natural sciences as well as engineering principles to develop and design new materials and establish the relation between internal structure and physical properties using experimental, computational and theoretical tools. 1 2 Merging the existing knowledge on physical properties, design limits and fabrication methods in materials selection for a particular application or to resolve material performance related problems. 2 3 Predicting and understanding the behavior of a material under use in a specific environment knowing the internal structure or vice versa. 1 Computer Science and Engineering Program Outcomes Area Electives 1 Design, implement, test, and evaluate a computer system, component, or algorithm to meet desired needs and to solve a computational problem. 1 2 Demonstrate knowledge of discrete mathematics and data structures. 2 3 Demonstrate knowledge of probability and statistics, including applications appropriate to computer science and engineering. 2
 Assessment Methods and Criteria Percentage (%) Final 30 Midterm 25 Exam 10 Participation 5 Group Project 30
 Recommended or Required Reading Textbook Discrete-event System Simulation, 5th Edition, Jerry Banks, John Carson, Barry L.Nelson, and David Nicol, Prentice Hall.Simulation With Arena, 5th Edition, W. David Kelton, Randall P. Sadowski, and DavidT. Sturrock, McGraw-Hill. Optional Readings Simulation modeling and analysis, Averill M. Law, W. David Kelton. Law, AverillM., Boston, McGraw-Hill, 2000.Handbook of simulation: principles, methodology, advances, applications, andpractice, edited by J. Banks, New York, Wiley, 1998.