COURSE UNIT TITLE

: SIMULATION OF MANUFACTURING SYSTEMS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IND 5034 SIMULATION OF MANUFACTURING SYSTEMS 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

INDUSTRIAL ENGINEERING (ENGLISH)
Industrial Engineering - Thesis (English) (Evening Program)
INDUSTRIAL ENGINEERING (ENGLISH)
INDUSTRIAL ENGINEERING - NON THESIS (ENGLISH)
INDUSTRIAL ENGINEERING - NON THESIS (EVENING PROGRAM) (ENGLISH)

Course Objective

The objective of this course is to introduce students fundamental concepts in simulation optimization, related statistics, and advanced concepts in a typical simulation software.

Learning Outcomes of the Course Unit

1   To be able to define simulation optimization
2   To be able to classify simulation optimization problems
3   To be able to integrate optimization meta heuristics with a simulation software
4   To be able to use ranking, selection and multiple comparisons procedures
5   To be able to use ARENA simulation software in detail

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 Introduction to simulation optimization
3 Output data analysis
4 Ranking and selection
5 Multiple comparison procedures
6 Simplex search
7 Mid term 1
8 Optimization meta heuristics and simulation software integration (1)
9 Optimization meta heuristics and simulation software integration (2)
10 Optimization meta heuristics and simulation software integration (3)
11 Optimization meta heuristics and simulation software integration (4)
12 Simulation optimization with multiple performance measures
13 Mid term 2
14 Response surface methodology

Recomended or Required Reading

Law, A.M. & Kelton, W.D., Simulation Modeling and Analysis, McGraw-Hill, 1992
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 12 3 36
Preparations before/after weekly lectures 12 4 48
Preparation for final exam 1 27 27
Preparing assignments 1 30 30
Preparation for midterm exam 2 25 50
Midterm 2 3 6
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.15245214
LO.232121
LO.322211
LO.433144
LO.552514