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Sistemi di Automazione
Automation Systems
Silvia Maria Zanoli

Seat Ingegneria
A.A. 2015/2016
Credits 9
Hours 72
Period I
Language ENG

Prerequisites
Discrete event systems basic definitions- Petri Nets

Learning outcomes
The student should : 1) learn:to evaluate the performance of an automated production system, through the use of Discrete Event Stochastic models, 2) acquire the ability to use appropriate simulation programs.

Program
It is expected that the student will be able to model Automated manufacturing Systems to evaluate its performance under uncerteinty conditions by means of Stochstic PN and Generalised SPN. Moreover it would be informed about advanced Architectures oc control systems for Process variables in industry. Therfore the topics addressed are: 1- Performances and performance indexes of AMS; 2Timed Petri Nets, stqates, enabling and firing conditions; analysis methods 3- Fundamentals of Markov processes and Generalaside Markov Processes characters. 4- SPN e GSPN characteristics and how to use them for performance evaluation of AMS 7 -Use of specific SW tools for the above topics Moreover information will be provided on: 8. . PID automatic setting. Implementation problems: : wind-up , mode swithcing. Kind of Process control systems: :series control, controllo feedforward controllo,Override, ratio control, controllo Split rangecontrollo. Exemples of commercially available process control systems.

Development of the examination
LEARNING EVALUATION METHODS
The assessment of student learning consists of two tests to evaluate the theoretical skills (written test and oral test) and a practical test of modeling and performance analysis of a discrete event system using stochastic timed models. The written test and the practical are in preparation for the oral exam. In case of failure of the oral exam, the student must also repeat the written test.

LEARNING EVALUATION CRITERIA
The evaluation the learning takes into account the results of verification tests / learning measurements and skills acquired and the ability to overcome any deficiency encountered by the results of the tests.

LEARNING MEASUREMENT CRITERIA
The measure of learning by means of written test is intended to assess the modeling skill for stochastic dynamic systems and the control techniques with advanced industrial controllers.To perform the written test a time limit is given. The measure of lea

FINAL MARK ALLOCATION CRITERIA
In order to pass the exam with a minimum score the student must have knowledge of all the course subjects. Further score will be awarded by demonstrating in-depth knowledge of the content of the course in the written and oral test s. The ”lode” is given to students who, having done all the tests correctly, have demonstrated a particular brilliance in the oral and in the preparation of written assignments and in the design activity.

Recommended reading
- Lecture notes - Ajmone Marsan M. et alii: “Modelling with Generalised Stochastic Petri Nets” John Wiley, 1994 For further readings the following texts are recommended: - Carlucci D., Menga G. “Teoria dei Sistemi ad eventi discreti” .UTET, Torino (1

Courses

• Ingegneria Informatica e dell'Automazione (Corso di Laurea Magistrale (DM 270/04))