COURSE UNIT TITLE

: COMPUTATIONAL INTELLIGENCE IN DESIGN AND MANUFACTURING

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
IND 5038 COMPUTATIONAL INTELLIGENCE IN DESIGN AND MANUFACTURING ELECTIVE 3 0 0 7

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR ADIL BAYKASOĞLU

Offered to

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

Course Objective

Teaching computational intelligence techniques and presenting their design and manufacturing applications to students with theoretical, computer applications and case studies. In this course computational intelligence techniques like fuzzy logic, neural networks, heuristic search will be presented. Their design and manufacturing applications will also be introduced with theoretical lectures, computer applications and case studies.

Learning Outcomes of the Course Unit

1   This course is expected to help the student to learn basic principles of computational intelligence techniques.
2   To enable students to solve complex engineering design and optimization problems by making use of computational intelligence techniques.
3   To enable students to develop computer programs to model and solve practical problems with computational intelligence techniques.
4   To enable students to carry out research studies on computational intelligence

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to computational intelligence
2 Introduction to Fuzzy Logic -1
3 Introduction to Fuzzy Logic -2
4 Introduction to Neural Networks -1
5 Introduction to Neural Networks -2
6 Introduction to Metaheuristic Search -1
7 Introduction to Metaheuristic Search -2
8 Fuzzy Logic applications in design
9 Fuzzy Logic applications in manufacturing
10 Midterm-1
11 Neural Networks Applications in Design and Manufacturing
12 Metaheuristic search Applications in Design
13 Metaheuristic search Applications in Manufacturing
14 Case study presentations and discussions

Recomended or Required Reading

1- Computational Intelligence in Design and Manufacturing, Andrew Kusiak, Wiley, 2000
2- Instructor s notes

Planned Learning Activities and Teaching Methods

Class presentations, case studies and practical applications

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 * 0.25 + ASG *0.25 +FIN *0.50
5 RST RESIT
6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.25 + ASG *0.25 +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)

Prof.Dr.Adil Baykasoğlu

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparation for midterm exam 1 15 15
Preparation for final exam 1 25 25
Preparations before/after weekly lectures 13 6 78
Preparing presentations 1 20 20
Midterm 1 3 3
Final 1 3 3
TOTAL WORKLOAD (hours) 183

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.133443433
LO.25334544343
LO.344433333
LO.433454333