The discrete events stochastic simulation
Learning a simulation language language (Simio or Arena)
Elaboration of a project work aimed to improve the performance of a production system by means of simulation.
Kelton, Law, Simulation modeling and analysis, McGraw Hill.
Kelton, Law, Sadowsky, Simulation with Arena, McGraw Hill
Learning Objectives
Learn how to model and simulate discrete event systems, by properly following the stesp of data acquisition, data processing, parameters estimation, model building, verification, validation and use in an statistically correct experimental frame.
Prerequisites
"Induatrial Plants Management" course
Teaching Methods
Lectures immediatly followed by training in IT laboratory or by means of BYOD
Further information
The laboratory is mandatory linked to "Management of Industrial Plants" course
Type of Assessment
Elaboration of a project work, about which the oral examination of "Industrial Plants Management" will be held
Course program
1) The discrete events stochastic simulation
1.a) taxonomies and definitions
1.b) The process modeling
1.c) The proper use of simulation as an experimental tool
1 d) The preparation of input data, and the analysis of results
1.e) The statistical methods for the analysis and comparison of results
1.f) The design of experiments
1.g) Learning a simulation language like Arena or Simio (to be decided)
2) Elaboration of a project work aimed to improve the performance of a production system by means of simulation.
2.a) Analysis of the pieces of information available on an industrial process
2 b) Definition of the scenarios on which to evaluate the performance and the related need for information
2.c) Process modeling
2.d) Definition and development of the simulation model in Arena or Simio (to be decided)
2.e) Preparation of input data
2.f) Conduuction of simulation experiments
2.g) Analysis of results and preparation of a technical report and an executive summary with recommendations for the executive officers of the plant