Politecnico di Torino
Politecnico di Torino
Politecnico di Torino
Academic Year 2017/18
Software architecture for automation
Master of science-level of the Bologna process in Computer Engineering - Torino
Master of science-level of the Bologna process in Mechatronic Engineering - Torino
Teacher Status SSD Les Ex Lab Tut Years teaching
Ghirardi Marco ORARIO RICEVIMENTO RC ING-INF/04 27 9 24 0 10
SSD CFU Activities Area context
ING-INF/04 6 B - Caratterizzanti Ingegneria informatica
Subject fundamentals
The course examines the automation software controlling a production system, which can be seen through several abstraction levels: logistics, long term planning, scheduling to the control of a single station. At each of those levels, a corresponding software must be able to receive and monitor the information on the state of the system , analyze them and to output commands in order to achieve a desired behavior, often optimizing one or more performance indexes.
This course is focused on the logistic and production planning levels, and its objective is to provide methods for modeling, simulating, and optimizing technical and economical performances indexes of logistic and production systems.
Expected learning outcomes
Simulative models of production systems development.
Modeling and solution methods for combinatorial optimization problems (mainly referring to production planning and scheduling problems)
Methods for production planning and control.
Prerequisites / Assumed knowledge
Suggested prerequisites are a basic knowledge of discrete event systems, linear programming models, and a good programming skill (C/C++ mainly).
- Automation, planning, scheduling.
- Scheduling theory basics.
- Simulation of logistic and production systems.
- Omnet++ (http://www.omnetpp.org/) : implementing simulation models.
- Combinatorial Optimization and Linear Programming models.
- Xpress software (http://www.fico.com/en/Products/DMTools/Pages/FICO-Xpress-Optimization-Suite.aspx) for solving PL models.
- Heuristic algorithms: greedy, local search, meta-heuristics (Tabu Search, Simulated Annealing, Genetic Algorithms, etc), Mat-heuristics.
- Specific scheduling problem examples.
- Multi-objective problems and Pareto analysis.
- Integration of an optimization-control software in a simulated system (dispatching rules, rolling horizon techniques, re-scheduling requests, etc).
- Real world application examples.
Delivery modes
A large course part will be devoted to laboratory activities, where two software will be used: Omnet++ for the implementation of simulation models, and FICO-Xpress as a tool for solving hard linear programming problems.
Texts, readings, handouts and other learning resources
The course is mainly based on the provided slides e course material.

Specific books for Discrete Event Simulation:
Carlucci, Menga, "Teoria dei sistemi ad eventi discreti", UTET 1998.
Cassandras, Lafortune, "Introduction to Discrete Event Systems", Springer.
G. Calafiore, "Elementi di Automatica", CLUT.

Specific books for Models and Algorithms for Combinatorial Optimization and Scheduling:
R. Tadei, F. Della Croce, "Elementi di Ricerca Operativa", Editrice Esculapio.
R. Tadei, F. Della Croce, A. Grosso, "Fondamenti di Ottimizzazione", Editrice Esculapio.
M. Ghirardi, A. Grosso, G. Perboli, "Esercizi di Ricerca Operativa", Editrice Esculapio.
Assessment and grading criteria
Mandatory output of the laboratories classes will be small group software projects for examples of automation systems. The evaluation will be through those project discussions and the written exam on the course program.
Optional, more challenging, laboratory works will be also considered for increasing the final mark.

Programma definitivo per l'A.A.2017/18

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