COURSE UNIT TITLE

: MODELING AND ANALYSIS OF DISCRETE EVENT SYSTEMS

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
END 4907 MODELING AND ANALYSIS OF DISCRETE EVENT SYSTEMS ELECTIVE 3 0 0 4

Offered By

Industrial Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR GONCA TUNÇEL MEMIŞ

Offered to

Industrial Engineering

Course Objective

Provide fundamental notions in modeling and analysis of discrete event systems and introduce general tools for modeling such systems (automata, Petri Nets, finite state machines) as well as methods for analyzing them (queuing systems). Present recent research in control of discrete event systems, mainly modeling, analysis and synthesis aspects.

Learning Outcomes of the Course Unit

1   To define the basic elements of system theory, then focuses on discrete event dynamic systems
2   To explain the mathematical properties of discrete event systems through Graph Theory and Petri Net models
3   To adopt the Petri nets theory and applications in problems of system modelling, design, and verification
4   To apply the above to the analysis of performance and reliability properties
5   To discuss the extension of discrete time towards continuous time and stochastic techniques, leading to, e.g., Markov chains, queuing models and stochastic Petri nets

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Brief review of basic notions from Systems Theory and its particularization for Discrete Event Systems
2 Brief review 2 Graph Theory
3 Essential Features of Petri Nets: Petri Net models and Definitions, CPN Tools I
4 Petri Net properties 1: Structural Methods and Invariants
5 Petri Net properties 2 : Behavioral Properties
6 State Space methods, Reachability Analysis
7 State Space Analysis: Heuristic Methods
8 Elementary Classes of Petri nets: Event (Marked) Graphs
9 Midterm Exam
10 Performance evaluation models: Timed PNs
11 Stochastic PNs, Markov Chains
12 Applications of Petri nets in Manufacturing Systems
13 CPN modelling tools
14 Presentation of Research Projects

Recomended or Required Reading

Textbook(s):
B. Hrúz and M.C. Zhou (2007), Modeling and Control of Discrete-event Dynamic Systems with Petri Nets and Other Tool , Springer-Verlag, London.
Proth, J.M. and Xie, X. (1996), Petri nets: A tool for design and management of manufacturing systems . Chichester, UK: John Wiley & Sons Inc.

Supplementary Book(s):
Jerry Banks, John Carson, Barry L. Nelson, and David Nicol (1994). Discrete-Event System Simulation , Fourth Edition by, Prentice Hall International Edition.
Zhou, M.C. and DiCesare, F. (1993), Petri Net Synthesis for Discrete Event Control of Manufacturing Systems , Norwell, Massachusetts: Kluwer Academic Publishers (1993).
Desrochers, A.A. and Al-Jaar, R.Y. (1995). Applications of Petri nets in Manufacturing Systems. New York, NY: Institute of Electrical and Electronics Engineers Press.
N. Viswanadham & Y. Narahari (1992) "Performance Modeling of Automated Manufacturing Systems", Prentice Hall.

Planned Learning Activities and Teaching Methods

Lectures, problem classes, worksheets, course notes, textbooks, web support.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE MTE*0.35+ASG *0.15+FIN * 0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE*0.35+ASG *0.15+RST * 0.50


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

Further Notes About Assessment Methods

None

Assessment Criteria

Mid-term (35%)+Homework (15%)+Final exam (50%)

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

E-mail: gonca.tuncel@deu.edu.tr; Telf: 02323017617

Office Hours

09:00-17:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 3 36
Preparation before/after weekly lectures 13 2 26
Preparation for Mid-term Exam 1 10 10
Preparation for Final Exam 1 14 14
Preparing Individual Assignments 2 4 8
Preparing Group Assignments 1 6 6
Preparing Presentations 1 4 4
Final 1 2 2
Mid-term 1 2 2
TOTAL WORKLOAD (hours) 108

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12
LO.143
LO.2444
LO.344544
LO.4455544
LO.5344333