SylabUZ
Nazwa przedmiotu | Modelling and simulation of production processes |
Kod przedmiotu | 06.9-WM-ZiIP-ZPU-ANG-D-16_20 |
Wydział | Wydział Mechaniczny |
Kierunek | Management and Production Engineering |
Profil | ogólnoakademicki |
Rodzaj studiów | drugiego stopnia z tyt. magistra inżyniera |
Semestr rozpoczęcia | semestr zimowy 2020/2021 |
Semestr | 2 |
Liczba punktów ECTS do zdobycia | 5 |
Typ przedmiotu | obowiązkowy |
Język nauczania | angielski |
Sylabus opracował |
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Forma zajęć | Liczba godzin w semestrze (stacjonarne) | Liczba godzin w tygodniu (stacjonarne) | Liczba godzin w semestrze (niestacjonarne) | Liczba godzin w tygodniu (niestacjonarne) | Forma zaliczenia |
Laboratorium | 30 | 2 | 18 | 1,2 | Zaliczenie na ocenę |
Wykład | 15 | 1 | 9 | 0,6 | Egzamin |
This is the transfer of basic knowledge and the acquisition of skills and competences in modelling and in the simulation of production processes; these will be used in further education and will be most useful in future, professional work.
Probability calculus, the basis of Computer Science, the organisation of production systems.
Lecture
Basic issues concerning conventional and flexible production systems. Model, modelling and simulation, simulation tools - a review. Mathematical programming issues in modelling. Methods for describing discrete processes. The theory of ‘mass handling’: single-and multi-channel systems; queue-free systems with queues; application intensity depending on the status of the system; optimisation in queue systems, the ‘Monte-Carlo’ method. Petri networks: action networks; position/transit networks; a formal description of networks; graph of reachable states; invariants; network viability and blocking; coloured networks; applications.
Laboratory
The real process versus the conceptual model. Linear discreet optimisation (integer) and zero-one programming methods for modelling production processes. ‘Queue system’ methods in modelling. Simulation of production processes, using queue networks. The ‘Monte-Carlo’ method and the generation of pseudo-random numbers. Simulation of simple and complex processes using Petri networks.
Lecture: a conventional lecture.
Laboratory: Laboratory work using available computer programmes.
Opis efektu | Symbole efektów | Metody weryfikacji | Forma zajęć |
Lecture: graded credit. The rating is issued based on a written exam covering the verification of the knowledge of the issues from the curriculum.
Laboratory: graded credit. The rating is determined based on the evaluation of skills related to the performance of laboratory tasks.
Final rating: the arithmetical mean of grades from individual types of classes.
Zmodyfikowane przez prof. dr hab. Taras Nahirnyy (ostatnia modyfikacja: 04-05-2020 15:07)