The main expected learning outcomes of the course, achievable through lectures and exercise sessions, consist of knowledge and comprehension of the main criteria and methods for the design of production systems, as well as of the practical abilities to analyze the features of different configurations and industrial technologies and to, correspondingly, synthesize design solutions.

In particular, the course will allow students to achieve knowledge and comprehension in order to:

• Name, with precise terminology, context, functions and processes implied within different configurations and design of production systems;
• Describe and explain the general features, strengths and weaknesses pertaining to different configurations of production systems, while relating, in each configuration, to different functions, processes and impacts on operational and business performances;
• Describe and explain the main criteria, approaches, methods and mathematical formulations to provide rough design solutions for different configurations of production systems;
• Describe and explain the modelling criteria and methods to provide detailed design solutions after performance assessment and verification in view of the stochastic nature of activities in production systems;
• Identify, describe and analyze the main features of some industrial technologies and their implications in terms of managerial and organizational issues.

The course will also allow students to be able to practically apply the acquired knowledge and comprehension in specific problem settings, proposed during the exercise sessions and requiring abilities of analysis and synthesis, leading to:

• Distinguish different contexts and requirements identified in specific problem settings, eventually being able to understand problems and opportunities in a given business and industrial environment and to formulate the goals in terms of performance targets and main design variables;
• Analyze the data sets provided within specific problem settings, to estimate the achievable performances and costs;
• Design solutions within different configurations of production systems, considering the contexts and the requirements due to specific problem settings, the achievable performances and costs.

The following topics are presented during the course:

1. analysis of the characteristics, scope, design, management and organizational issues of the different configurations of production systems;
2. criteria, approaches and methods for the design of manufacturing systems (job shop, manufacturing cells, transfer lines);
3. criteria, approaches and methods for the design of manual assembly systems (fixed position assembly, paced and un-paced lines, continuous flow lines, multi-model and mixed-model lines, assembly shop, assembly cells);
4. criteria, approaches and methods for the design of automated assembly systems (lines, flexible assembly systems);
5. criteria, approaches and methods for the design of process plants;
6. analysis of some industrial technologies (e.g.: food, paper, cement, ceramics, glass, semiconductors) and related management and organizational issues;
7. criteria and methods for performance assessment and verification of design solutions in view of the stochastic nature of activities in production systems (factory physics principles and laws, Monte Carlo and Discrete Event simulation applied to manufacturing processes and systems).

For students coming from other universities or other Bacs than Management Engineering, it is suggested to have a background in production and operations management. Such a background can be retrieved also accessing the Operations Management MOOC  provided by Politecnico di Milano in the Polimi Open Knowledge (POK) platform.

The examination consists of a written examination on the content of the lectures and exercise sessions and of an oral examination as optional. A manufacturing system design case will be required in order to access the oral examination; the case will consist of an extended exercise providing a specific problem setting that the student will have to face through the analysis and synthesis of possible design solutions.

Overall, the student will have to demonstrate, during the exam, his/her learning outcomes as proper knowledge and comprehension of the main criteria and methods for the design of production systems, as well as of the practical abilities required to analyze the features of different configurations and industrial technologies and to, correspondingly, synthesize proper design solutions.

In particular, during the exam, the students will have to:

• be able to introduce, with precise terminology, the context, functions and processes implied within different configurations of production systems;
• be able to describe and explain the general features, strengths and weaknesses of different configurations of production systems, showing an understanding of the motivations at the background;
• be able to describe and explain, in each configuration of production system, the different functions and processes as well as the expected impacts on operational and business performances of different design solutions;
• be able to describe and explain the main criteria, approaches, methods and mathematical formulations, and their usage to provide rough design solutions for different configurations of production systems;
• be able to describe and explain the modelling criteria and methods, and their usage to provide detailed design solutions after performance assessment and verification in view of the stochastic nature of activities in production systems;
• be able to identify, describe and analyze the main features of some industrial technologies and their implications in terms of managerial and organizational issues;
• be able to distinguish different contexts and requirements identified in specific problem settings as well as to analyze the data sets provided to estimate the achievable performances and costs; 
• be able to provide design solutions within different configurations of production systems, considering the requirements due to specific problem settings, the achievable performances and costs.