AIMS AND CONTENT

LEARNING OUTCOMES

The student acquires the general criteria and methodologies for the feasibility study, design and construction of industrial plants.

AIMS AND LEARNING OUTCOMES

Attendance and active participation in the proposed training activities and individual study will allow the student at the end of the course to: 

• Know the specific set of new IT tools to support production processes, distinguishing functionalities and application contexts
• Know and manage problems in the implementation of information systems to support production processes.
• Understand the application of the tools to real use cases for different industries. 
• Know and understand the simulation techniques of industrial plants and complex production systems
• Build and statistically validate DES simulation models in stochastic regime
• Know the main optimization techniques applied to stochastic simulation

TEACHING METHODS

The topics will be developed approximately on 12 weeks of frontal lessons divided into two days of lessons per week. The lessons will be held with the support of power point presentations and held in Italian.  

SYLLABUS/CONTENT

Tools and methodology for plant and production systems management (Professor Prof. Marco Gotelli, 20 hours)

Digital innovation

• What is meant by digitization of processes
• Operational management of digitization projects
• Structure of a process digitization project
• Drafting of final documentation

Process Management Tools

• Traditional tools for process management
• Generic and customized ERP software
• Tools for logistics and warehouse management
• Specific tools for production management, product life cycle (MES, scheduler, PLM)

Capabilities and use cases of IT tools in the enterprise

• ERP (Enterprise Resource Planning)
• MES (Manufacturing Execution system)
• PLM (Product Lifecycle Management)

System Integration

• Connection with ERP and schedulers
• MES - ERP integration
• Direct connection to machinery and Industry 4.0. 
• Use of efficiency data and feedback to the factory.
• Typical difficulties in the adoption of information tools and errors to avoid. 

Tools and methodology for the sizing and optimization of plants and production systems (Lecturer Prof. Lucia Cassettari, 34 hours)

Simulation techniques and application contexts

• Discrete Event Simulation
• System Dynamics
• Agent Based Simulation
• Monte Carlo Simulation

Statistical validation methods of stochastic simulation models

• Evolving time systems
• Evolving run systems

Experimental Design applied to simulation

• Regression theory
• Response Surface Methodology (RSM)

Optimal search techniques for simulated systems

• Steepest Ascent/Descent
• Simplex Method and variants
• Nature Inspired Heuristic

Practical exercise of building a DES simulation model and applying design techniques of experiments

RECOMMENDED READING/BIBLIOGRAPHY

All the slides used during the lessons and other teaching material will be available on the teaching Teams channel. The notes taken during the lessons and the material on Teams are sufficient for the preparation of the exam

TEACHERS AND EXAM BOARD

LESSONS

LESSONS START

https://corsi.unige.it/en/corsi/8734/studenti-orario

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The exam includes an oral interview with both teachers of the course. Each teacher will verify the student's preparation for the part of the program of his competence. 
To participate in the oral exam you must register for the official exam sessions on the https://servizionline.unige.it/studenti/esami/prenotazione website.

ASSESSMENT METHODS

The oral exam will allow to check the capability of the student of reasoning  and connecting different concepts with each other.The quality of the exposition, the correct use of the specialist vocabulary, the ability of critical reasoning will also be assessed.