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

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

The course is based on lectures and classworks, with the blended approach. Guest international speakers will be invited to give special lectures. In agreement with the blended approach, the students should attend normally two online classes and maximum one in-presence class each week. The in-presence class may be repeated to ensure the possibility for the students to attend.

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.

None.

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.

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