Master of science-level of the Bologna process in Mechatronic Engineering (Ingegneria Meccatronica) - Torino Master of science-level of the Bologna process in Ingegneria Informatica (Computer Engineering) - Torino
Giudizio sulla descrizione delle modalitą di esame: Soddisfacente
Descrizione degli obiettivi che l'esame intende accertare, coerentemente con i "risultati di apprendimenti attesi" dichiarati: Assente
Commenti sulla descrizione delle modalitą di esame Per la prova scritta occorre indicare la possibilitą di uso di materiale didattico (libri, appunti, ...) durante la prova. MANCA la descrizione degli obiettivi che l'esame intende accertare, si consiglia di fare riferimento alle linee guida ed esempi riportati nella procedura di proposte schede insegnamento.
Giudizio complessivo sulla scheda
Commenti scheda La scheda si presenta completa in ogni sua parte. Occorre inserire la descrizione degli obiettivi che l'esame intende accertare. Si consiglia di inserire il numero delle ore o di CFU dedicati ai singoli argomenti indicati nel quadro Course topics.
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, production planning and detailed production scheduling levels, and its objective is to provide methods for modeling, simulating, and optimizing technical and economical performances indexes of logistic and production systems.
- Know how to model a combinatorial optimization problem through a linear programming model.
- Know the main solution methods and algorithms for combinatorial optimization problems, both exact and heuristic.
- Know how to define and effectively approach production planning and scheduling problems.
- Know the basics of discrete event simulation, with the goal of simulating a production systems.
- Learn to use a simulative model of an automated production system and to implement a scheduler able to optimize the production efficiency.
- Introduction: Automation, planning, scheduling.
- Combinatorial Optimization and Linear Programming models with examples in production planning and logistics.
- Xpress software (https://www.fico.com/en/products/fico-xpress-optimization) for solving LP models.
- Scheduling theory basics.
- Simulation of logistic and production systems.
- Omnet++ (http://www.omnetpp.org/) : implementing and using simulation models.
- Combinatorial Optimization : exact algorithms.
- Combinatorial Optimization: heuristic algorithms (Greedy, Local Search, Metaheuristics, Tabu Search, Simulated Annealing, Genetic Algorithms, Matheuristics).
- Specific production scheduling problem examples.
- Laboratory: integration of an optimization-control scheduling software in a simulated system.
- 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 simulating production system models, and FICO-Xpress as a tool for solving hard scheduling problems. The students will solve optimization problems and develop a scheduler and integrate it to the simulation model, with the goal of improving the production system efficiency.
Note that It is possible to install Omnet++ and a student version of XPress on personal PCs, in order to work on the laboratory exercises at home as well.
The course is mainly based on the provided slides e course material.
Specific books for Models and Algorithms for Combinatorial Optimization and Scheduling:
M. Pinedo, "Scheduling: Theory, Algorithms, and Systems", Springer.
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.
Specific books for Discrete Event Simulation:
Cassandras, Lafortune, "Introduction to Discrete Event Systems", Springer.
G. Calafiore, "Elementi di Automatica", CLUT.
Carlucci, Menga, "Teoria dei sistemi ad eventi discreti", UTET 1998.
Modalitą di esame: Prova scritta (in aula); Elaborato progettuale individuale; Elaborato progettuale in gruppo;
Exam: Written test; Individual project; Group project;
The exam is written, and based on a set of questions and exercises, with the objective of verifying the above mentioned competences (Expected Learning Outcomes). The exam duration is 1,5 hours. This exam gives a maximum of 20 points (minimum 10 for passing). The laboratory activities give a maximum of 12 points. The final evaluation is the sum of the points obtained with the exam and the laboratory project (with 31 being still 30, and 32 being 30L).
Gli studenti e le studentesse con disabilitą o con Disturbi Specifici di Apprendimento (DSA), oltre alla segnalazione tramite procedura informatizzata, sono invitati a comunicare anche direttamente al/la docente titolare dell'insegnamento, con un preavviso non inferiore ad una settimana dall'avvio della sessione d'esame, gli strumenti compensativi concordati con l'Unitą Special Needs, al fine di permettere al/la docente la declinazione pił idonea in riferimento alla specifica tipologia di esame.
Exam: Written test; Individual project; Group project;
The exam is written, and based on a set of questions and exercises, with the objective of verifying the above mentioned competences (Expected Learning Outcomes). The exam duration is 1,5 hours and it is open-book.
The exam gives a maximum of 22 points (minimum 12 for passing). The laboratory activities give a maximum of 10 points. The final evaluation is the sum of the points obtained with the exam and the laboratory project (with 31 being still 30, and 32 being 30L).
In addition to the message sent by the online system, students with disabilities or Specific Learning Disorders (SLD) are invited to directly inform the professor in charge of the course about the special arrangements for the exam that have been agreed with the Special Needs Unit. The professor has to be informed at least one week before the beginning of the examination session in order to provide students with the most suitable arrangements for each specific type of exam.