Modeling and analysis of mining systems using discrete-event simulation:
▪ Introduction to discrete-event simulation
▪ Random and pseudo-random numbers
▪ Sampling and parameter estimation
▪ Variance reduction techniques
▪ Input modeling
▪ Simulation with arena
▪ Simulation of mining systems
- Teacher: Θεόδωρος Μιχαλακόπουλος
ECTS : 4
Language : el
Learning Outcomes : Upon successful completion of the course, the student will be able to: recognize a discrete event system describe the quantitative, qualitative and operational relationships between the units that constitute a mining system distinguish the prerequisites, application fields and limitations of the method distinguish the differences between sequences of random and pseudo-random numbers select an appropriate statistical distribution for modeling input data develop empirical statistical distributions select appropriate system performance measures develop a simulation model of the studied system on the computer interpret simulation results evaluate the performance of mining systems compare alternative mining systems.