Industrial Engineering

Numerical Analysis(ING218)

Content
Course Code Course Name Semester Theory Practice Lab Credit ECTS
ING218 Numerical Analysis 3 2 1 0 2.5 4
Prerequisites
Admission Requirements
Language of Instruction French
Course Type Compulsory
Course Level Bachelor Degree
Course Instructor(s) Temel ÖNCAN ytoncan1@gsu.edu.tr (Email)
Assistant Ufuk BAHÇECİ ubahceci@gsu.edu.tr (Email)
Objective This course, which is offered as an elective course to Industrial Engineering students, introduces students to solution techniques for numerical problems.Students will gain basic knowledge and skills for numerical solution of the problems they will encounter both in business life and during their academic careers. In this context, we can list the objectives of this course as follows:

Giving ideas about numerical analysis problems,
To provide general information about the scope and difficulties of numerical analysis problems,
To provide basic knowledge about solution techniques of numerical analysis problems,
To provide students with the ability to apply complex numerical analysis, solving techniques and typesetting operations.
Content Introduction to Numerical Analysis
Computer arithmetic and errors in numerical solutions
Introduction to Matlab programming
Solving nonlinear equations
Bisection method and Newton’s method
Solving a system of linear equations
LU decomposition
Iterative methodes Jacobi and Gauss-Seidel
Curve fitting
Interpolating polynomials
Least-square method
Numerical differentiation, Taylor Series Expansions
Numerical Integration,
Trapezoidal method , Simpson’s method
Course Learning Outcomes The student who successfully completes this course:
- Gained an overview of numerical analysis problems
- Can suggest approaches to solving numerical analysis problems
- Can list new approaches and concepts from the field of numerical analysis
- Have basic programming skills with MATLAB
- Can find the roots of functions computationally
- Can solve systems of equations computationally
- Can perform derivative and integral operations computationally
Teaching and Learning Methods
References Gilat, A., Subramaniam,V., “Numerical Methods for Engineers and Scientists: An Introduction with Applications Using MATLAB”, 3rd ed 2013 Wiley, Hoboken, NJ, USA.

Quarteroni, A., Sacco, R. Saleri, F., Methodes Numeriques: Algorithmes, analyse et applications, Springer, 2007, Milano, Italy.

Merrien, J-L., Analyse Numerique: Avec MATLAB, Dunod, 2007, Paris, France.
Print the course contents
Weekly Contents
Theory Topics
Week Weekly Contents
1 Introduction to Numerical Analysis
2 Computer arithmetic and errors in numerical solutions
3 Introduction to Matlab programming
4 Solving nonlinear equations
5 Bisection method and Newton’s method
6 Solving a system of linear equations
7 Midterm
8 LU decomposition
9 Iterative methodes Jacobi and Gauss-Seidel
10 Curve fitting
11 Interpolating polynomials
12 Least-square method
13 Numerical differentiation, Taylor Series Expansions
14 Numerical Integration, Trapezoidal method , Simpson’s method
Practice Topics
Week Weekly Contents
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Assessment System
Contribution to Overall Grade
  Number Contribution
Contribution of in-term studies to overall grade 0 0
Contribution of final exam to overall grade 1 40
Toplam 1 40
In-Term Studies
  Number Contribution
Assignments 0 0
Presentation 0 0
Midterm Examinations (including preparation) 1 30
Project 0 0
Laboratory 0 0
Other Applications 0 0
Quiz 2 30
Term Paper/ Project 0 0
Portfolio Study 0 0
Reports 0 0
Learning Diary 0 0
Thesis/ Project 0 0
Seminar 0 0
Other 0 0
Toplam 3 60
Relation of Proficiency
No Program Learning Outcomes Contribution
1 2 3 4 5
1 Knowledge and understanding of a wide range of basic sciences (math, physics, ...) and the main concepts of engineering X
2 Ability to combine the knowledge and skills to solve engineering problems and provide reliable solutions X
3 Ability to select and apply methods of analysis and modeling to ask, reformulate and solve the complex problems of industrial engineering X
4 Ability to conceptualize complex systems, processes or products under practical constraints to improve their performance, ability to use innovative methods of design X
5 Ability to design, select and apply methods and tools needed to solve problems related to the practice of industrial engineering, ability to use computer technology X
6 Ability to design experiments, collect and interpret data and analyze results X
7 Ability to work independently, ability to participate in working groups and have a multidisciplinary team spirit
8 Ability to communicate effectively, ability to speak at least two foreign languages X
9 Awareness of the need for continuous improvement of lifelong learning, ability to keep abreast of scientific and technological developments to use the tools of information management
10 Awareness of professional and ethical responsibility X
11 Knowledge of the concepts of professional life as "project management", "risk management" and "management of change"
12 Knowledge on entrepreneurship, innovation and sustainability
13 Understanding of the effects of Industrial Engineering applications on global and social health, environment and safety.
14 Knowledge of the problems of contemporary society
15 Knowledge of the legal implications of the practice of industrial engineering
ECTS
Activities Number Period Total Workload
Class Hours 14 3 42
Working Hours out of Class 13 3 39
Midterm Examinations (including preparation) 1 6 6
Final Examinations (including preparation) 1 10 10
Quiz 2 3 6
Total Workload 103
Total Workload / 25 4.12
Credits ECTS 4
© Copyright 2016 - IT Office
Scroll to Top