The European Master in Sustainable Systems Engineering (EMSSE)

EMSSE places a special emphasis on Sustainable Systems Engineering, equipping students with the knowledge and skills to create systems that are efficient, cost-effective, and environmentally friendly. We prioritize considering the environmental, economic, and social impacts of a system throughout its entire lifecycle, from design and development to operation and maintenance.

The overarching objective of EMSSE is to design pioneering career paths and curricula for future SE professionals. Our program offers a specific student mobility agreement and three distinct paths, focusing on Systems Engineering (SoSE — University of Genoa), methodology in Prediction and Optimization Strategies for SE (AOS — University of Technology of Compiègne), and Manufacturing Systems (AMS — Polytechnique University of Catalunya). Graduates receive a joint degree signed by all partner HEIs, alongside a joint diploma supplement.

The uniqueness and the added value of this master program stands in:

• Integration of 3 European and 1 Western Balkans HEI with outstanding connections with industrial partners to propose a more complete and top-quality multidisciplinary academic knowledge in SE.
• A compulsory semester (M1S2) for all EMSSE students will take place in Polytechnique University of Tirana and teaching will be realized by all HEIs.
• Training of highly qualified personnel having interdisciplinary skills and expertise in SE with multiple external opportunities in different countries.
• High involvement of world leader industries representing a key factor for the training of new professional and opening to an international agenda.

Academic structure and content overview

EMSSE is a new training initiative that seeks to propose a complete programme covering all Systems Engineering components, with a specific emphasis on sustainability and innovation.

The academic path comprises two academic years (120 ECTS credits). Each year is split into two semesters, indicated hereinafter as MxSy where Mx (i.e., M1 and M2) is referred to the year of study and Sy (i.e., S1 and S2) is referred to the specific semester of that year. The program of the first year is devoted to establishing a deep and jointly designed background on SE topics. Moreover, during M1S1, each HEI will offer language courses to be attended by all students, whereas during M1S2, a course  will be devoted to public speaking, collaborative working, and project-based learning.

The second year is aimed at providing EMSSE students with a specialization related to three relevant SE areas. Then, in the second year, the course teaching is structured around three academic paths, covering the following three main areas of system engineering:

Path1: SoSE — Systems of Systems Engineering led by UniGe

This training path addresses and analyses the methods and tools for designing and implementing methods and software tools working behind autonomous mutually interacting systems, i.e., systems of systems (SoS). These systems generally show capabilities related to perception, communication, learning, decision-making and action, and are able to interact with their environment and with similar systems. They must also handle numerous sources of uncertainty that can impact performance and, consequently, monitor the performance and the behavior of the whole system. More specifically, this training path aims at providing modelling and methodological approaches to sensing, actuation, and control in order to describe and analyses a system, and take decisions based on the available data in a distributed, predictive and/or adaptive manner, thereby performing “smart actions”. The student will approach such smart systems by studying proper models and methods in different application contexts, such as connected autonomous vehicles and platooning, drones, smart power grids and energy efficient buildings, distributed logistics, and environmental monitoring. The first semester of second year will take place at UNIGE, which have full potential of experimental platforms and recognized research/teaching teams in this field.

There are two mobility paths for SoSE:

• Mobility path 1 (UTC-UPT-UniGe) ;
• Mobility path 2 (UPC-UPT- UniGe).

Path 2: AOS — Advanced machine learning and Optimisation of Systems led by UTC

This training path focuses on learning theory/practice and optimization, as applied to autonomous interacting technology-intensive systems. The focus will be in decision making and decision support in the context of complex systems with advanced optimization methods also capable of treating the presence of uncertainty. The applications will refer to ‘autonomous vehicles able to communicate with each other, to smart transport system infrastructures, to airborne mini drones, and to sensor networks that exchange data in real time, to logistic warehouses needing for prediction real-time data analysis, simulation and optimization. The platforms available in the Heudiasyc Laboratory (autonomous vehicle, virtual reality, railway simulator or mini drones) are at disposal of master students. The studied systems implement machine learning, decision-making and action capabilities, while interacting with their environment and other systems. The first semester of second year will take place at UTC, which is successfully experiencing a master specialization track, combining optimization and machine learning.

There are two mobility paths for AOS:

• Mobility path1 (UPC-UPT-UTC) ;
• Mobility path 2 (UniGe-UPT-UTC).

Path 3: AMS — Advanced Manufacturing Systems led by UPC

Today’s society demands breakthrough technologies in emerging areas as digital industry and smart factories. Facing such challenges requires that interdisciplinary engineering teams work together to come up with creative, reliable, ethical and sustainable solutions. One of the key factors in leading successful projects is for professionals from different areas to have strong skills in modern engineering methods such as big data, 3D printing, smart sensors, and computer simulation. This training path has been designed to enhance students’ academic background with such skills, thus preparing them for the future. The specializations will allow them to face real problems in the emerging area of smart factories. During the training path, planning, scheduling and control problems will be formalized and solved according to the framework proposed by the ANSI/ISA-95 international standard. Special focus will be devoted to the primary and support functions given by the Manufacturing Execution System (MES). At the end of the training path, the student will be able to position an industrial automation problem in the context of ANSI/ISA-95 and to formalize and to solve decision-making problems, using proper methods and tools. The first semester of second year will mostly take place at UPC which is fully equipped for experimentation and have also a long successful experience on this area.

There are two mobility paths for AMS:

• Mobility path1 (UTC-UPT-UPC) ;
• Mobility path 2 (UniGe-UPT-UPC).

In the last semester M2S2, students have the opportunity to work on their Master Thesis in the most suitable context for their project, which can be a “research lab environment” or a company in which the student can perform an internship period.

Mobility

The students’ mobility mostly depends on the chosen academic path. Specifically, the academic path defines the university where students spend the second year of the programme. Then, the second year of SoSE path will be realized at UNIGE, for AOS it will take place at UTC and for AMS, students will stay at UPC.

The first semester of the first year (M1S1) takes place in one of the two EU universities not already associated with the chosen academic path, whereas all students spend the second semester of the first year (M1S2) at UPT in Tirana, where they acquire other common competencies and they have the opportunity to develop the EMSSE community with a common culture.