 | Study programme 2019-2020 | Français | |
| Discrete Event Systems | |||
Learning Activity |
| Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) | Establishment |
|---|---|---|---|---|
| I-TCTS-100 |
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| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
|---|---|---|---|---|---|---|---|
| Anglais | Anglais | 14 | 22 | 0 | 0 | 0 | Q1 |
| Organisational online arrangements for the end of Q3 2019-2020 assessments (Covid-19) |
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| Description of the modifications to the Q3 2019-2020 online assessment procedures (Covid-19) |
| time-limited individual production |
Content of Learning Activity
REVIEW OF SYSTEM THEORY FUNDAMENTALS: Basic concepts, Time-driven vs. event-driven systems, Examples of Discrete Event Systems (DES): automated manufacturing; traffic systems, The queueing system model. UNTIMED MODELS OF DISCRETE-EVENT SYSTEMS, State Automata, Analysis: stability, reachability, deadlocks. The Poisson counting process and Markov chain models INTRODUCTION TO DISCRETE EVENT (MONTE-CARLO) SIMULATION, Basic concepts in discrete event simulation, Model construction and applications, Introduction to estimation theory MARKOV DECISION PROCESSES. Solving resource contention problems: admission control, routing, scheduling
Grafcet Model and process design.
Required Learning Resources/Tools
Not applicable
Recommended Learning Resources/Tools
Not applicable
Other Recommended Reading
Not applicable
Mode of delivery
- Face to face
Type of Teaching Activity/Activities
- Cours magistraux
- Exercices dirigés
- Utilisation de logiciels
- Travaux pratiques
- Etudes de cas
Evaluations
The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)