COURSE UNIT TITLE

: INDUSTRIAL APPLICATIONS OF SIMULATION

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
ENM 5012 INDUSTRIAL APPLICATIONS OF SIMULATION ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR GÖKALP YILDIZ

Offered to

Logistics Engineering (Non-Thesis-Evening)
ENGINEERING MANAGEMENT- NON THESIS (EVENING PROGRAM)
Logistics Engineering

Course Objective

The objective of this course is to introduce students fundamental concepts in discrete event system simulation, related statistics, and basic modelling concepts in a typical simulation software.

Learning Outcomes of the Course Unit

1   To be able to define components of a system
2   To be able to define basic statistics in order to carry out a typical simulation study
3   To be able to develop a simulation model of a system
4   To be able to analyze the input/output data
5   To be able to use ARENA simulation software

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to simulation
2 Monte Carlo simulation (1)
3 Monte Carlo simulation (2)
4 Selecting input probability distributions
5 Random number generation
6 Random variate generation
7 Mid term 1
8 Output analysis (1)
9 Output analysis (2)
10 Simulation modelling with ARENA (1)
11 Simulation modelling with ARENA (2)
12 Simulation modelling with ARENA (3)
13 Simulation modelling with ARENA (4)
14 Variance reduction techniques

Recomended or Required Reading

Pegden, C. Dennis, Shannon, Robert E., Sadowski, Randall P., 1995, Introduction to Simulation Using SIMAN, Mc. Graw-Hill, Inc.
Kelton, W. David, Sadowski, Randall P., Sturrock, David T., 2007, Simulation With ARENA, McGraw-Hill.
Rossetti, Manuel D., 2009, Simulation Modeling and ARENA, Wiley.
Banks J., Carson J., Nelson B., Nicol D., 2001, Discrete-Event System Simulation, Prentice Hall.

Planned Learning Activities and Teaching Methods

Instructor notes will be given using blackboard and visual presentations. In addition to this, laboratory studies will be carried out and group projects will be given.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE MTE * 0.50 + FIN * 0.50
4 RST RESIT
5 FCGR FINAL COURSE GRADE MTE * 0.50 + RST * 0.50


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

gokalp.yildiz@deu.edu.tr, Tel. +90-232-3017614

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparations before/after weekly lectures 13 5 65
Preparation for midterm exam 1 45 45
Preparation for final exam 1 45 45
Midterm 1 3 3
Final 1 3 3
TOTAL WORKLOAD (hours) 200

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.1545345
LO.24344234
LO.3334544
LO.444355532
LO.5345322