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

ASISTANT PROFESSOR SEREN ÖZMEHMET TAŞAN

Offered to

INDUSTRIAL ENGINEERING - NON THESIS
INDUSTRIAL ENGINEERING
INDUSTRIAL ENGINEERING
INDUSTRIAL ENGINEERING - NON THESIS (EVENING PROGRAM)

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   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 Bernoulli Process
4 Poisson Process
5 Poisson Process
6 Markov Chains
7 Markov Chains
8 Markov Chains
9 Markov Processes
10 Markov Processes
11 Mid-Term Exam
12 Project Assignment
13 Project Assignment
14 Project Assignment

Recomended or Required Reading

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 and seminar 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 ASG ASSIGNMENT
2 MTE MIDTERM EXAM
3 FIN FINAL EXAM
4 FCG FINAL COURSE GRADE ASG * 0.30 + MTE * 0.30 + FIN * 0.40
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) ASG * 0.30 + MTE * 0.30 + RST * 0.40


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)

latif.salum@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 1 2 2
Mid-term 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.143345
LO.23443
LO.354343
LO.43443
LO.534345

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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