OVERVIEW

The course provides the methodological tools for the representation, analysis and management of industrial automation systems, with specific reference to the class of discrete production systems. For that class of systems, several decision problems are defined and dealt with, in connection with a hierarchical decision framework which includes four decision levels: the strategic level, the tactical level, the operational level, and the real-time control level.

AIMS AND CONTENT

LEARNING OUTCOMES

The course provides methods and tools to analyse the performance of discrete production systems (manufacturing systems) and to solve decision problems at strategic, planning and operational levels.

AIMS AND LEARNING OUTCOMES

At the end of the course, the student will be able to suitably represent the dynamics of a discrete production system and to analyse its behaviour through the application of some specific models and methods. The student will be also able to solve some decision problems, in particular tactical-operational planning problems, such as those related to scheduling decisions.

TEACHING METHODS

The lectures are mainly realized in the classroom, with some lessons in lab in order to learn about specific software

SYLLABUS/CONTENT

Introduction - Discrete production systems - Introduction to models and methods for strategic and tactical planning - Scheduling: key performance indicators, classification, solution algorithms and optimization models - Models and methods for the analysis of the system behaviour at the operational level of discrete-event systems

RECOMMENDED READING/BIBLIOGRAPHY

S. Nahmias, Production and Operations Analysis, Irwin, 1989

M.L. Pinedo, Scheduling. Theory, Algorithms, and Systems, Springer, 2008

S. French, Sequencing and Scheduling, Ellis Horwood Ltd., 1982

C.G. Cassandras, S. Lafortune, Introduction to Discrete Event Systems, Springer, 1999

A. Di Febbraro, A. Giua, Sistemi ad eventi discreti, McGraw-Hill, 2002

J. Banks, J.S. Carson II, B.L. Nelson, D.M. Nicol, Discrete-Event System Simulation, Prentice Hall, 2010

TEACHERS AND EXAM BOARD

Exam Board

MAURO GAGGERO (President)

SILVIA SIRI (President)

SIMONA SACONE

LESSONS

LESSONS START

Monday, February 20th, 2017.

Class schedule

MODELS AND METHODS FOR AUTOMATION

EXAMS

EXAM DESCRIPTION

The exam is composed of two parts, one written and one oral. In the written part, the students should solve 2-3 exercises. It is possible to take the oral exam if the mark of the written part is equal or greater than 18. 

ASSESSMENT METHODS

During the written exam, the student should be able to apply, to numerica cases, the methods and algorithms of the course. During the oral exam, the student should demonstrate to have learnt the methods presented in the course and to be able to apply such methods in real applicative cases. 

Exam schedule