ID: 1579
Course type: theoretical and methodological
Course coordinator: Nedeljković M. Dušan
Lecturers: Nedeljković M. Dušan
Contact: Nedeljković M. Dušan
Level of studies: M.Sc. (graduate) Academic Studies – Mechanical Engineering
ECTS: 6
Final exam type: oral
Department: Department of Production Engineering
The objective of this course is that students: acquire knowledge and skills necessary for practical problems solving in manufacturing automation using computer simulation; to master the methods used for computer simulation modeling and implementation in manufacturing automation; to obtain the knowledge about the systematic approach to the project of computer simulation in manufacturing automation; to develop critical approach to the effects of computer simulation application in automation; to get familiar with the role of computer simulation within digital factory.
After successfully completing this course, the students should be capable to: - Create and implement stochastic simulation; - Create conceptual model for discrete event simulation; - Create and implement discrete event simulation within fixed and flexible automation framework; - Create conceptual and computer model for continuous simulation of various processes; - Integrate continuous and discrete event simulation; - Manage discrete event simulation project.
1. Introduction to computer simulation: simulation objectives; advantages and disadvantages of simulation; phases of computer simulation development; computer simulation in manufacturing automation; a variety of simulation models: continuous and discrete models, deterministic and stochastic simulation 2. Stochastic simulation: sampling methods, random numbers, random number generators, Monte Carlo simulation 3. Discrete event simulation: elements of discrete event simulation, conceptual modeling of discrete event simulation, activity cycle diagram 4. Computer models for discrete event simulation: approaches in model coding: activity based approach, event based approach, process based approach, the three phase approach; comparative analysis of different approaches 5. Discrete event simulation software: general purpose programming languages, application oriented simulation software; definition of simulation model in programming languages and simulation software packages; simulation outputs and results presentation; application of computer graphics and animation in simulation; application examples of simulation software 6. Discrete event simulation application in automation: generation of conceptual and computer models of fixed, programmable and flexible automation 7. Discrete event simulation project: system definition, generation of simulation model, model verification and validation, simulation experiments, results presentation and documentation 8. Continuous system simulation: continuous systems modeling, basic principles of numerical integration, modeling of the examples of continuous systems in manufacturing automation, programming languages and software for continuous system simulation, integration of continuous simulation into discrete event simulation 9. Digital factory and simulation: concept and models of digital factory; the role of simulation in digital factory: plant design and optimization, operational management and optimization
Laboratory exercises: 1. Monte Carlo simulation 2. Discrete event simulation software: ARENA – basic functioning principles and simulation examples 3. Discrete event modeling and simulation: examples of fixed and flexible automation 4. Continuous systems simulation: modeling and simulation of specific examples in the area of manufacturing automation using general purpose programming language and in application oriented simulation software – ARENA Discrete event simulation project: Students work on project dealing with the development of a simulation of a chosen flexible manufacturing system. During project realization students systematically implement all phases of discrete event simulation project: conceptual modeling, model coding, animation generation, model verification and validation, experimentation, analysis of the simulation results. The output is the report and project presentation at the end of semester.
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Jakovljevic, Z., Computer simulаtion in manufacturing automation – lecture handouts Computer classroom – each student individually works on a computer Arena Simulation Software by Rockwell Automation General purpose programming language
Total assigned hours: 75
New material: 20
Elaboration and examples (recapitulation): 10
Auditory exercises: 0
Laboratory exercises: 20
Calculation tasks: 0
Seminar paper: 0
Project: 10
Consultations: 0
Discussion/workshop: 0
Research study work: 0
Review and grading of calculation tasks: 0
Review and grading of lab reports: 1
Review and grading of seminar papers: 0
Review and grading of the project: 1
Test: 0
Test: 8
Final exam: 5
Activity during lectures: 5
Test/test: 30
Laboratory practice: 15
Calculation tasks: 0
Seminar paper: 0
Project: 20
Final exam: 30
Requirement for taking the exam (required number of points): 30
Carrie, A., Simulation of Manufacturing Systems, John Willey and Sons, New York, 1988; Robinson, S., Simulation: The Practice of Model Development and Use, John Willey and Sons, New York, 2004; Pidd, M., Computer Simulation in Management Science, John Willey and Sons, New York, 2004; Kelton, D., V., et al., Simulation with Arena, McGraw-Hill, 2009; Cellier, F., E., Kofman, E., Continuous System Simulation, Springer, New York, 2006