Search results: 1877
- Teacher: Elif Binboga
- Teacher: Francine Kafwata
- Teacher: Junior Tshitembo
- Teacher: Francine Kafwata
- Teacher: Nidai Kordal
- Teacher: Junior Tshitembo
THIS COURSE AIMS TO HELP INDUSTRIAL ENGINEERING STUDENTS TO UNDERSTAND FUNDAMENTAL CONCEPT OF PROBABILITY THEORY AND GAIN THE ABILITY TO USE METHODS OF THE DISCIPLINE. THE MAIN CONTENT INCLUDES INTRODUCING THE PROBABILITY THEORY - GIVING PRIORITY TO RANDOM VARIABLES RELATED TO UNCERTAIN EVENTS; ENSURING THAT STUDENTS HAVE A DEEP UNDERSTANDING OF PROBABILITY DISTRIBUTIONS AND THEIR IMPLICATIONS IN INDUSTRIAL ENGINEERING; HELPING THE STUDENTS TO USE PROBABILITY THEORY TO BUILD AND ANALYZE INDUSTRIAL ENGINEERING MODELS/PROBLEMS ENCOUNTERED IN REAL LIFE, ESPECIALLY FOR THE PROBLEMS INCLUDING UNCERTAINTY.
- Teacher: Elif Binboga
- Teacher: Francine Kafwata
- Teacher: Junior Tshitembo
- Teacher: Ayse Tuncbilek
- Teacher: Francine Kafwata
- Teacher: Mazyar Nejad
- Teacher: Junior Tshitembo
Advanced simulation modeling-concept in process interaction orientation. Modeling of Manufacturing Systems, Station Submodels, Dynamic/Static simulation, Mixed Simulation Models is included. Introductory output analysis, comparison of alternatives and/or experimentation are discussed. Mainly Rockwell Arena and Microsoft Excel is helpful for applications (depending on what type of simulation is on the table.
- Teacher: Elif Binboga
The aim of this course is to improve the skills of students in modeling and solving real life problems in the mathematical programming and optimization. Both deterministic and stochastic models are considered. The course objective is to study the mathematical programming techniques ,to develop various and complex models on the real-world situations, to give an invaluable skill that will help students in other courses and in the workplace.
- Teacher: Ayse Tuncbilek