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Scheda Riassuntiva
Anno Accademico 2019/2020
Scuola Scuola di Ingegneria Industriale e dell'Informazione
Insegnamento 055014 - SMART MANUFACTURING LAB
  • 055013 - SMART MANUFACTURING LAB [2]
Docente Macchi Marco
Cfu 5.00 Tipo insegnamento Modulo Di Corso Strutturato

Corso di Studi Codice Piano di Studio preventivamente approvato Da (compreso) A (escluso) Insegnamento
Ing Ind - Inf (Mag.)(ord. 270) - BV (479) MANAGEMENT ENGINEERING - INGEGNERIA GESTIONALE*AZZZZ055014 - SMART MANUFACTURING LAB

Obiettivi dell'insegnamento

The aim of the course is to provide the students an opportunity to face real problems in real manufacturing environments through the application of smart manufacturing methods to support the engineering and management of high-value-added products, the continuous innovation of products and processes, the sustainability of products and production systems along their lifecycle.

The smart manufacturing approaches exploited in the course will focus on complex manufacturing challenges addressing products, production process, systems and their continuous evolution, entailing a wider engineering perspective.

The integrated Smart Manufacturing Lab (5+10 CFU) will pursue this perspective to tackle manufacturing problems like the design and reconfiguration of manufacturing systems, zero-waste and sustainable solutions for manufacturing, integrated product-process approaches for personalization, advanced planning and scheduling in complex and uncertain environments, prognostics and health management of manufactured assets, reliability and availability improvement in manufacturing systems.

 

The students will have the opportunity to take advantage of smart manufacturing methods and tools and experimental experience to solve real industrial problems through the “action-based learning” approach used in the “learning factory”. Moreover, the students will enhance their capability to interact in a professional environment in a responsible and constructive way, working in a group, planning and coordinating roles and activities within the group, and interacting with a company providing the context where the real problem is set and solved.

The course fits into the overall program curriculum pursuing some of the defined general learning goals. In particular, the course contributes to the development of the following capabilities:

  • Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modeling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment;
  • Develop new ideas and solutions in business and industrial scenarios evolving over time;
  • Interact in a professional, responsible, effective and constructive way in a working environment, also motivating group members.

Risultati di apprendimento attesi

The main expected learning outcomes of the course, achievable through a mix of activities aimed at implementing the “action-based learning” (Seminars/Lectures, Lab experience, Industrial Internship, Real data modeling and analysis), consist of knowledge and comprehension of the smart manufacturing methods and the practical abilities to use them in the context of real industrial environments. In particular, the course will allow students to achieve knowledge and comprehension in order to:

1. Analyze and model a real problem in a real manufacturing environment, understanding the relevant elements and influencing factors, defining proper modelling hypothesis, collecting information and data;

2. Select and apply smart manufacturing methods to real industrial cases, coping with incomplete and/or unreliable information and data;

3. Work and cooperate in a team and interact with a company;

4. Plan and manage their work grounding on the intermediate results and the evolution of the context;

5. Explain, communicate and motivate the work done.


Argomenti trattati

Starting from a real industrial case, a set of engineering problems will be defined, addressing the range of typical problems a manufacturing company has to face in a multidisciplinary way by a group of students spending about 5 weeks in a company, with the aim at exploiting the tools and methods learned to analyze, formalize and provide a solution to it.

Possible framework engineering problems will be:

  • the design and implementation of a Prognostics and Health Management process aimed to implement Condition Based/Predictive Maintenance;
  • the performance analysis of a manufacturing system to improve the reliability, availability and overall equipment/factory effectiveness along the life cycle; 
  • the implementation of Total Cost of Ownership to support planning and monitoring of manufacturing assets along their life cycle.

 

The following activities will be carried out: 

Industrial Internship: all the students will be given the opportunity to spend a period of internship in the company proposing the manufacturing problem under study. The period will be organized as an internship through the Career Service.

Seminars/Lectures: seminars/lectures will be organized to deepen all the technological and management aspects connected to the problem under study.

Lab experience: specific problems will be addressed by the students by directly using labs and facilities at the Department of Mechanical Engineering, Department of Industrial Engineering as well as other facilities working in close relation with Politecnico di Milano.

Real data modelling and analysis: data collected in real industrial contexts will be provided and used to design and/or validate the solutions provided.


Prerequisiti

Industrial engineering methods and tools addressed in the previous courses.

An assessment exercise for soft-skills and group-work attitudes is suggested (check the offer provided by the Career Service).


Modalità di valutazione

The assessment for the course is operated by means of:

  • A report related to the project work. (group, learning outcome 1-2-4-5)
  • An intermediate and final presentation of the work done including a final video. (individual,learning outcome 5)
  • A report provided by the company hosting the internship. (individual, learning outcome 3-4)

Bibliografia

Forme didattiche
Tipo Forma Didattica Ore di attività svolte in aula
(hh:mm)
Ore di studio autonome
(hh:mm)
Lezione
12:00
18:00
Esercitazione
6:00
9:00
Laboratorio Informatico
5:00
0:00
Laboratorio Sperimentale
0:00
0:00
Laboratorio Di Progetto
15:00
60:00
Totale 38:00 87:00

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese
Disponibilità di materiale didattico/slides in lingua inglese
Disponibilità di libri di testo/bibliografia in lingua inglese
Possibilità di sostenere l'esame in lingua inglese
Disponibilità di supporto didattico in lingua inglese
schedaincarico v. 1.6.5 / 1.6.5
Area Servizi ICT
30/09/2020