Founded in 2003, AXEAL, a digital and industrialisation engineer, is positioned as a specialist in the energy, defence and aeronautics sectors.
Its ability to bring together high-potential teams, coupled with its technological solutions from its Peatwhee R&D centre, enables AXEAL to offer its customers relevant solutions in response to today’s major challenges.
Its employees, men and women, engineers and technicians, recognised as much for their operational expertise as for their sense of commitment, are at the heart of the company’s success and provide complete satisfaction to its customers.
INDUSTRIAL PROJECT MANAGER
The client needed to be accompanied on :
The industrialisation of a new container for the Rafale.
• Transfer of 3D models.
• Preparation of the definition for production.
• Tooling design.
Axeal was in charge of :
• Preparation of the production package.
• Preparation of the assembly lines
• The design of assembly tools.
• Establishing and monitoring the project schedule.
MISSION THROTTLE CONTROL QUADRANT
The initial customer requirement was to develop a 4-lever throttle with auto-pilot function.
The tasks were to develop the test benches necessary for the functional tests as well as the tests for the qualification campaign
The mission was then completed by the function of mechanical engineer to carry out static and kinematic calculations of the joystick. Work on the redesign of the joystick following the initial validation tests was carried out.
SYSTEM ELECTRIFICATION - MOBILITY
The request of the client :
Making an electric urban vehicle with swappable batteries.
We did :
• Study of a new electrical vehicle concept
• Buil a new architecture
• define a storage system
• Integrate conntected services
The objective is the integration of a predictive maintenance application on a new machine park of 6 machining centres in order to anticipate and reduce the unavailability rates of the automatic workshop.
• Machine Learning algortihms
• Weak signal processing for rotating machinery without IOT
Machine Health / Process Integrity
1. Classic threshold monitoring
2. Signal processing
3. Machine Learning
To propose an application to manage medical emergency scenarios for long manned flights, related to physical exercise, nutrition and health.
The scenarios concern uro-sceptic shock, stroke, heart attack, phlebitis, etc.
• Machine Learning Algorithms
• NLP vocal synthesis
• Modelling and use cases in space-based emergency medicine
Safety software standards NASA