At the end of this course, the students; 1) Use Mathematica effectively 2) Optimizasyon uygulamaları yapabilir. 3) Develop system simulation model 4) Use basic industrial engineering functions
MODE OF DELIVERY
Face to face
PRE-REQUISITES OF THE COURSE
No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT
COURSE DEFINITION
COURSE CONTENTS
WEEK
TOPICS
1st Week
Basics of Mathematica: Stephen Wolfram, Aritmetic, basic functions, basic graphics, basic rules
2nd Week
Algebra in Mathematica: Equations
3rd Week
Mathematica Interfaces: Menus, Documents, Rules
4th Week
Lineer Algebra: Vectors and matrices
5th Week
Calculus: Series, Derivative, Integral
6th Week
Diferantial equations
7th Week
Visual Operations in Mathematica: Graphics, interactive interfaces
8th Week
Midterm
9th Week
Methodological and List Based Programming: Cycles, Lists
10th Week
User-Defined Functions in Mathematica
11th Week
Data Analysis with Mathematica: Optimization, Data Manipulation, Curve Fitting, Statistics
12th Week
Optimization applications
13th Week
System modelling
14th Week
Introducing Functions of Basic Industrial Engineering Applications
RECOMENDED OR REQUIRED READING
S.Dick, A.Riddle.D.Stein, Mathematica in the Laboratory, Cambridge University Press, 1997. M.L. Abell, J.P. Braselton, L.M. Braselton, A Beginner?s Guide to Mathematica, 2002.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
Presentation,Experiment
ASSESSMENT METHODS AND CRITERIA
Quantity
Percentage(%)
Mid-term
1
20
Quiz
1
25
Project
1
25
Total(%)
70
Contribution of In-term Studies to Overall Grade(%)
70
Contribution of Final Examination to Overall Grade(%)
30
Total(%)
100
ECTS WORKLOAD
Activities
Number
Hours
Workload
Midterm exam
1
2
2
Preparation for Quiz
1
14
14
Individual or group work
14
13
182
Preparation for Final exam
1
25
25
Course hours
14
3
42
Preparation for Midterm exam
1
25
25
Laboratory (including preparation)
Final exam
1
2
2
Homework
1
14
14
Total Workload
306
Total Workload / 30
10,2
ECTS Credits of the Course
10
LANGUAGE OF INSTRUCTION
Turkish
WORK PLACEMENT(S)
No
KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)