Ing Ind - Inf (Mag.)(ord. 270) - BV (479) MANAGEMENT ENGINEERING - INGEGNERIA GESTIONALE

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054202 - MANUFACTURING SYSTEMS ENGINEERING I

054952 - MANUFACTURING SYSTEMS ENGINEERING II

054201 - MANUFACTURING SYSTEMS ENGINEERING

Ing Ind - Inf (Mag.)(ord. 270) - BV (483) MECHANICAL ENGINEERING - INGEGNERIA MECCANICA

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054201 - MANUFACTURING SYSTEMS ENGINEERING

Obiettivi dell'insegnamento

Manufacturing companies must be able to design and modify their production systems which are continuously evolving together with the products they produce. The course provides a framework, quantitative methods and relevant competences to design manufacturing systems and to manage their lifecycle in coordination with the lifecycle of products and processes in order to enhance the industrial competitiveness. Mathematical models of manufacturing systems will be studied to evaluate the performance and optimize the configuration. Different mathematical models will be applied according to the characteristics of manufacturing systems and the relevant assumptions.

In the scope of the Learning Goals of the Master of Science in Management Engineering, the goals of the course are:

Understand context, functions, processes in a business and industrial environment and the impact of those factors on business performance

Identify trends, technologies and key methodologies in a specific domain (specialization streams)

Design solutions applying a scientific and engineering approach (Analysis, Learning, Reasoning, and Modelling capability deriving from a solid and rigorous multidisciplinary background) to face problems and opportunities in a business and industrial environment

Risultati di apprendimento attesi

After passing the exam, the student will be able to:

Understand the current manufacturing context

Illustrate the key strategic and technological trends in the manufacturing industry

Understand the co-evolution of products, processes and production systems

Analyse production problems and formalize the requirements for manufacturing systems

Identify, compare and select production system architectures

Plan the acquisition of production capacity

Develop models of manufacturing systems based on a mathematical representation of their characteristics and behaviour and according to the required level of detail.

Identify, select, and implement mathematical methodologies to support the design, management and control of manufacturing systems

Optimize the configuration and control of manufacturing systems and estimate their performance

After completing the optional project work, the student will be able to:

Write a technical project report

Present the results achieved during the analysis, modelling and testing activities

Argomenti trattati

Manufacturing Strategy and business models related to the coevolution of product, process and system. Manufacturing systems lifecycle. Strategic and technical aspects of flexibility and reconfigurability. Examples of flexible and reconfigurable manufacturing/de-manufacturing systems. New business models. Production systems architectures.

Strategic design of Manufacturing systems. Analytic Hierarchy Process (AHP) for decision support in multi-criteria and multi-objective contexts. Stochastic programming techniques for the design of evolving manufacturing systems considering uncertainty and multiple objectives; modelling of future scenarios.

Design of Manufacturing systems. Introduction to methods for performance evaluation of complex manufacturing systems. Optimization of the configuration of manufacturing systems based on the quantitative results of performance evaluation. Gradient-based methods for the optimization of manufacturing systems.

Technical design of Manufacturing systems. Relations between technological specifications and production system types. State-based modelling of manufacturing systems. Continuous-time Markov chains to model simple manufacturing systems. Analytical methods (queueing networks) to model complex productions systems and estimate key performance indicators. Approximate analytical methods to model unreliable manufacturing systems and evaluate their performance. Decomposition techniques to evaluate the performance of long flowlines.

Design of Manufacturing Systems Control. Optimization of token based production policies. Hedging point policies.

Analysis of real production systems.

Prerequisiti

None.

Modalità di valutazione

The assessment will be based on a final exam (written test) that consists of 2 or 3 practical and theoretical exercises. Practical exercises will assess the ability to understand and analyse realistic industrial problems and then develop models to apply methodologies aimed at designing manufacturing systems and evaluating the impact of possible reconfigurations. Theoretical exercises will ask to elaborate on concepts, models, techniques and methodologies presented during the course.

After passing the written test, students will be given the possibility to improve the final grade through:

optional oral exam on theoretical and practical questions related to the topics included in the course program (max 3 points).

optional project work (max 3 points). The work will focus either on the application of a methodology to a real industrial case or the further development of a methodology studied during the course.

optional homeworks that will be assigned and evaluated during the course (max 1 point). The assignments consist in the implementation in Matlab code of algorithms related to the program.

However, a maximum of 4 points can be added to the grade of the written test.

The course will offer lectures and class-works. Class-works will be held in computer-lab for applying methodologies and tools to manufacturing systems engineering problems. A visit to an industrial plant will be organized.

Bibliografia

Professor's Noteshttps://beep.metid.polimi.it/web/108910323L. Saaty, Fundamentals of Decision Making and Priority Theory with the Analytic Hierarchy Process, Editore: RWS Publications, Pittsburg, PA, USA, Anno edizione: 1994, ISBN: 0-9620317-6-3 Note:

Suggested pages: IX-XIV; 1-43

J.R. Birge, F. Louveaux, Introduction to Stochastic Programming, Editore: Springer - Verlag New York, Anno edizione: 1997, ISBN: 0-387-98217-5 Note:

A. Di Gennaro, A. Giua, Sistemi ad eventi discreti, Editore: McGraw-Hill, Anno edizione: 2002, ISBN: 88-386-0863-6 Note:

Suggested pages: 83-129

D.D. Yao, Stochastic Modeling and Analysis of Manufacturing Systems, Editore: Springer Verlag New York, Anno edizione: 1994, ISBN: 3-540-94319-6 Note:

Suggested pages: 1-13

J.A. Buzacott, J.G. Shanthikumar, Stochastic Models of Manufacturing Systems, Editore: Springer Verlag New York, Anno edizione: 1994, ISBN: 3-540-94319-6 Note:

Suggested pages: 1-13

S.B. Gershwin, Manufacturing Systems Engineering, Editore: Prentice-Hall, Anno edizione: 1994 Note:

Suggested pages: XVII-XIX; 1-18; 59-99

Software utilizzato

Nessun software richiesto

Forme didattiche

Tipo Forma Didattica

Ore di attività svolte in aula

(hh:mm)

Ore di studio autonome

(hh:mm)

Lezione

60:00

90:00

Esercitazione

40:00

60:00

Laboratorio Informatico

0:00

0:00

Laboratorio Sperimentale

0:00

0:00

Laboratorio Di Progetto

0:00

0:00

Totale

100:00

150:00

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