COURSE UNIT TITLE

: PERFORMANCE ANALYSIS OF MANUFACTURING SYSTEMS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IND 5035 PERFORMANCE ANALYSIS 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

ASSOCIATE PROFESSOR SEREN ÖZMEHMET TAŞAN

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

This course aims to enable students to use stochastic processes and Markov Chains in modeling and analysis of manufacturing systems.

Learning Outcomes of the Course Unit

1   Describe the basics of stochastic processes
2   Demonstrate the difficulties of analytical modelling in real world manufacturing systems
3   Analyse a manufacturing system in transition state
4   Analyse a manufacturing system steady state
5   Analyse transfer lines, assembly/disassembly systems, real time scheduling models
6   Discuss their applicability

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Probability Spaces and Random Variables
2 Probability Spaces and Random Variables
3 Markov chains
4 Transfer lines in manufacturing systems
5 Models and boundaries for transfer lines
6 Deterministic transfer model
7 Stockastic transfer modes
8 Stokastic transfer models
9 Stokastic transfer models
10 Assembly/disassembly models
11 Real time scheduling models
12 Project Presentations
13 Project Presentations
14 Project Presentations

Recomended or Required Reading

C. Cassandras and S. Lafortune, Introduction to Discrete Event Systems, Springer, 2007
S.B. Gershwin, Manufacturing Systems Engineering, Prentice Hall, 1994.
M. Puterman, Markov decision processes, John Wiley & Sons, 1994
D.P. Bertsekas, Dynamic Programming, Prentice Hall, 1987
J. Li and S.M. Meerkov, Production Systems Engineering, WingSpan PRESS, 2008
E. Çınlar, Introduction to Stochastic Processes, Prentice-Hall, 1975
N. Viswanadham and Y. Narahari, Performance Modeling of Automated Manufacturing Systems, Prentice Hall, 1992

Planned Learning Activities and Teaching Methods

The course is taught in a lecture, class presentation and discussion format. All class members are expected to attend both the lecture hours and take part in the discussion sessions. Besides the taught lecture, group presentations are to be prepared by the groups.

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 * 0.20 + ASG * 0.20 + FIN * 0.60
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.20 + ASG * 0.20 + RST * 0.60


Further Notes About Assessment Methods

None

Assessment Criteria

Mid Term (%20) + Assignment (%20) + Final (%60)

Language of Instruction

English

Course Policies and Rules

To be announced

Contact Details for the Lecturer(s)

Asst. Prof.Dr. Seren OZMEHMET TAŞAN
seren.ozmehmet@deu.edu.tr

Office Hours

To be announced

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 3 36
Preparation before/after weekly lectures 12 3 36
Preparing Individual Assignments 1 10 10
Preparing presentations 1 40 40
Office hours 12 3 36
Preparation for midterm exam 1 20 20
Preparation for Final Exam 1 18 18
Final Assignment 1 2 2
Project Assignment 1 2 2
TOTAL WORKLOAD (hours) 200

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.1342134353
LO.2415523142
LO.3133244321
LO.43243552433
LO.5311342345
LO.65555555555

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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