Joint courses co-designed under JUMP project: Multi-Agent systems for Smart Machining

The JUMP project has progressively strengthened engagement with external stakeholders, including companies, clusters and public authorities. CBL activities enabled stakeholders to contribute real-world challenges, improving alignment between education and socio-economic needs. The initial collaborations have established a basis for sustained co-creation and in the second phase of the project the JUMP project partners (initially INSA Toulouse and University of Trento) have initiated the co-design of joint courses.

1. The first Micro-module was:

JUMP Multi-Agent Systems for Smart Machining I
Prediction and Monitoring (link)

The micromodule introduces the students to the smart machining and the power of the Industrial Internet of Things (IIoT) and Multi-Agent systems. During this first Module, students learn how to design a monitoring system for machining process and how to collect data from distributed devices, with practical experiences; the data so obtained are stored in a database and become the subject matter of the second module (described below).

Study period: 6 October – 31 October 2025
‍Study format: Online
‍Credits: 1 ECTS
‍Hosting university: INSA Toulouse

2. In the end of 2025, a Challenge was offered:

Multi-Agent Systems for Smart Machining II
Reduce Energy Consumption in the Manufacturing Process (link)

The challenge forms part of the MASSMa programme, delivered by INSA Toulouse and University od Trento. In this challenge, monitoring tools were used, along with the Industrial Internet of Things (IIoT) and multi-agent systems to solve a problem faced by industry: reducing the energy consumption of a manufacturing process.

Study period: 1 December 2025 – 20 February 2026
‍Study format: Blended
‍Credits: 2 ECTS
‍Hosting university: INSA Toulouse

3. In the spring semester the second co-designed micro-module was hosted by University of Trento.

Multi-Agent Systems for Smart Machining III
Machine-Learning models for data analysis, classification and prediction of process conditions (link)

This is the second part of a course that started with the module I offered by INSA Group. During the first Module, students learn how to design a monitoring system for machining processes and how to collect data from distributed devices. The data obtained are stored in a database and become the subject matter of the second module, where the students learn to develop machine learning models (classical and AI-based) to classify the process condition and to make predictions on the process itself.

Students participating to this course shall be able to build custom algorithms for analyzing and classifying manufacturing process data, by designing the algorithms, mangling and organizing the data in the database/data-lake, training and validating the models, and deploying the trained model to operations.

Study period: 1 March – 30 April 2026
‍Study format: Online
Credits: 3 ECTS
‍Hosting university: University of Trento