OVERVIEW

The course concerns the main topics related to the classification of discrete event production systems. Models of production processes at the operational and control decision-making level will be presented. Moreover, optimization of push and pull production systems will be defined.

AIMS AND CONTENT

LEARNING OUTCOMES

Knowing analytical and simulation techniques for evaluating the main performance indexes of complex dynamic processes; understanding the features of a decisional problem, as regards the decisional variables, the objective functions and all the constraints on decisions; stating and solving decisional problems oriented at an effective organization of processes, with reference to the hierarchical decisional structure including strategic, tactical, and operational levels; using software tools for planning frameworks

AIMS AND LEARNING OUTCOMES

The learning outcomes of the course refer to the capacity of:

• − knowing the features of discrete production processes;
• − algorithm definition for discrete event simulation;
• − scheduling design and application;
• − definition and optimization of push and pull production systems.

TEACHING METHODS

The course consists of lessons during which the theoretical contents of the course are presented together with the solution of numerical cases and the use of some software frameworks related to the course topics.

SYLLABUS/CONTENT

• • Information system models of a manufacturing company
• • Manufacturing process models
  • o The decisional / functional architecture of manufacturing processes
  • o System production design
• • Simulation o Dynamic models with discrete events
  • o Discrete events simulation algorithms
  • o An example: Simulation of a manufacturing process modeled as an open queue network
  • o Generation of random inputs o Statistical analysis of the results of simulated experiments
  • o Introduction to some programming language used in discrete events simulation
• • System production scheduling
  • o Definition o Single-machine scheduling
  • o Parallel machine scheduling
  • o Flow-shop scheduling
  • o Job-shop scheduling
• • MRP, MRPII and ERP Systems
  • o Definition and Models (Make to Order, Make to Stock)
  • o Introduction to Basic Problems at Planning Level
  • Demand Prediction Basic Example
  • o Inventory Control Basic Example

RECOMMENDED READING/BIBLIOGRAPHY

Bruno, G. (2005). Operations management: modelli e metodi per la logistica. Edizioni scientifiche italiane.

TEACHERS AND EXAM BOARD

Exam Board

ENRICO ZERO (President)

ROBERTO SACILE

SIMONA SACONE (President Substitute)

LESSONS

LESSONS START

https://corsi.unige.it/en/corsi/10716/studenti-orario

EXAMS

EXAM DESCRIPTION

The exam consists of an evaluation of a group project and an oral test with open questions on the course topics

ASSESSMENT METHODS

The exam is composed by a project and oral part. During the exam the student has to present the main arguments of the course, to solve numerical exercises and to explain the theoretical notions necessary for their solution.

Exam schedule

FURTHER INFORMATION

Students with disabilities or with DSA can request compensatory/dispensatory measures for the exam. The methods will be defined on a case-by-case basis together with the Engineering Contact of the University Committee for the support of disabled students and those with DSA. Students who wish to request it are invited to contact the course teacher well in advance by copying the Engineering Contact (https://unige.it/commissioni/comitatoperlassociazionedeglistudenticondisabilita.html), without sending documents regarding their disability.