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Software architecture for automation

01PECOV, 01PECQW

A.A. 2019/20

Course Language

English

Course degree

Master of science-level of the Bologna process in Computer Engineering - Torino
Master of science-level of the Bologna process in Mechatronic Engineering - Torino

Course structure
Teaching Hours
Lezioni 36
Esercitazioni in laboratorio 24
Teachers
Teacher Status SSD h.Les h.Ex h.Lab h.Tut Years teaching
Ghirardi Marco Ricercatore ING-INF/04 18 0 36 0 7
Teaching assistant
Espandi

Context
SSD CFU Activities Area context
ING-INF/04 6 B - Caratterizzanti Ingegneria informatica
2018/19
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.
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.
Learn to model and acquire knowledge about the main solution methods for combinatorial optimization problems. Know how to effectively approach production planning and scheduling problems. Know the basics methods for production control systems. Learn to use a simulative model of an automated production system.
Learn to model and acquire knowledge about the main solution methods for combinatorial optimization problems. Know how to effectively approach production planning and scheduling problems. Know the basics methods for production control systems. Learn to use a simulative model of an automated production system.
Suggested prerequisites are a basic knowledge of discrete event systems, linear programming models, and a good programming skill (C/C++ mainly).
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.
- 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.
The course is based on classes, where theory and examples will be presented, and laboratory activities. In the laboratory two software will be used: Omnet++ for the implementation of simulation models, and FICO-Xpress as a tool for solving hard scheduling problems.
The course is based on classes, where theory and examples will be presented, and laboratory activities. In the laboratory two software will be used: Omnet++ for the implementation of simulation models, and FICO-Xpress as a tool for solving hard scheduling problems.
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.
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.
ModalitÓ di esame: prova scritta; progetto di gruppo;
The exam is written, giving a maximum of 20 points (minimum 10 for passing) and it is composed by 2-3 numerical exercises. The duration of the exam is 1h30m and it is open book. A mandatory group project based on the laboratory experiences (implementation of an automated production scheduler and testing in a simulated environment) gives a maximum of 13 points.
Exam: written test; group project;
The exam is written, giving a maximum of 20 points (minimum 10 for passing) and it is composed by 2-3 numerical exercises. The duration of the exam is 1h30m and it is open book. A mandatory group project based on the laboratory experiences (implementation of an automated production scheduler and testing in a simulated environment) gives a maximum of 13 points.


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