MASSMa Pathway returns for 2026–2027 with INSA Toulouse and the University of Trento

After a first edition in 2025–2026, INSA Toulouse and the University of Trento are building on their collaboration through JUMP by offering the European Manufacturing for Smart Machining (MASSMa) pathway again in 2026–2027.

The renewed pathway brings together two online micro-modules and an industrial challenge. Students can earn up to 8 ECTS by completing all three activities :

• Multi-Agent System for Smart Machining, Part I: Monitoring - Online micro-module - INSA Toulouse‍
• Multi-Agent System for Smart Machining PART II: Reducing Energy in Machining - Blended challenge - INSA Toulouse ‍
• Multi-Agent System for Smart Machining 2 : Machine- learning models for data analysis, classification and prediction of process conditions - Online micro-module - University of Trento

The pathway puts JUMP’s responsible innovation objectives into practice through a concrete industrial question: how can a machining process use less energy while maintaining performance? Students learn to collect and interpret machining data, then use that evidence to identify where energy savings may be possible. The spring micro-module extends this work by introducing tools for analysing data and predicting process conditions.

1.    Multi-Agent System for Smart Machining, Part I: Monitoring

• Online micro-module
• INSA Toulouse · 2 ECTS · 1 October–13 November 2026

In the first micro-module, students explore how the Industrial Internet of Things and multi-agent systems can be used to monitor machining processes. They learn how to collect data from connected devices and use it to understand what is happening during machining.

2.  Multi-Agent System for Smart Machining PART II: Reducing Energy in Machining

1. Blended challenge
2. INSA Toulouse · 3 ECTS · 16 November–16 December 2026

The challenge builds on the monitoring skills introduced in the first micro-module. Working on an industrial case proposed by the challenge provider Pad’Occ, students use machining data and monitoring tools to identify ways to reduce energy consumption while maintaining process performance. The challenge combines online work with a mobility week in Toulouse.

3.  Micro-Module Multi-Agent System for Smart Machining 2 : Machine- learning models for data analysis, classification and prediction of process conditions:

• Online micro-module
• University of Trento · 3 ECTS · Spring 2027 (application dates to come)

In the spring micro-module, students learn how machine-learning models can help them analyse machining data, classify process conditions and make predictions. This gives them a further way to interpret the data that monitoring systems collect.

Students can take the micro-modules separately or combine them with the industrial challenge to complete the full pathway. For current availability and participation requirements, visit : https://engage.eciu.eu/

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