Ing Ind - Inf (Mag.)(ord. 270) - BV (479) MANAGEMENT ENGINEERING - INGEGNERIA GESTIONALE
097311 - MANUFACTURING SYSTEMS ENGINEERING
Ing Ind - Inf (Mag.)(ord. 270) - BV (483) MECHANICAL ENGINEERING - INGEGNERIA MECCANICA
097311 - MANUFACTURING SYSTEMS ENGINEERING
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.
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:
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 Modeling 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
Identify, compare and select production system architectures
Analyse production problems and formalize the requirements for manufacturing systems
Plan the acquisition of production capacity
Develop models of manufacturing systems
Identify, select, and implement mathematical methodologies to support the design and management 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
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.
Technical design of Manufacturing systems. Relations between technological specifications and production system types. Continuous-time Markov chains and analytical methods to model productions systems and estimate key performance indicators. Approximate analytical methods to evaluate the performance of complex manufacturing systems. Gradient-based methods for the optimization of manufacturing systems.
Design of Manufacturing Systems Control. Optimization of token based production policies. Hedging point policies.
Analysis of real production systems.
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.
Professor's Notes on BeeP platform https://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:
Pagine consigliate: 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: