Simulation languages and animation are covered. Statistical inference is used to draw conclusions and to identify the best system. Test of hypothesis, nonparametric statistics, simple linear regression and correlation, multiple linear regression, analysis of variance and factorial experiments. Basic simulation modeling concepts, discrete and continuous simulation models are studied. Collection and analysis of data, use of analytical techniques, verification and validation models, random number generation methods, and system design issues are included in order to enhance the ability of the students to apply mathematical knowledge in the simulation area.
Statistical inference is used to draw conclusions and to identify the best system.
Handouts and lecture notes will be partially available on the website of the course. The students will learn how to identify, formulate and then to solve manufacturing system simulation problems. The course aims to provide a sound base with the techniques, tools, and methods it provides for engineering practice.