Aeronautics
The project focused on the development of highly automated on-line and off-line inspection and control technologies for production processes, which have enabled a significant reduction in production costs, increasing the competitiveness of the industrial partners in the project.
The MAIPCO project concerns defect analysis in the production of complex composite components in the aeronautical sector and has developed new methodologies to reduce these defects.
1. An automatic artificial vision and signal analysis system with robotic movement (AVRIS) for the validation of assemblies (fuselage, transmission systems, stabilizer, fin);
2. The AVRIS System automatically identifies the presence / absence of the parts, their correct installation and the presence of the fixings.
EnginSoft was involved in developing a methodology to manage the paths of Remote Piloted Aircraft Systems with respect to unforeseen events.
DTA - DISTRETTO TECNOLOGICO AEROSPAZIALE, AGUSTA WESTLAND, ALENIA AERMACCHI SPA, CETMA - TECHNOLOGIES DESIGN AND MATERIALS EUROPEAN RESEARCH CENTRE, ENGINSOFT SPA, UNIVERSITÀ DEL SALENTO
Funding Scheme MIUR Programma Operativo Nazionale (PON 03) “Ricerca e Competitività” | Call identifier MIUR DD 713/Ric. Del 29/10/2013
28 months
2015 - 2018
Distretto Tecnologico Aerospaziale (DTA) scarl
Vito Primavera
6
Some of our competences in research and technology transfer
Research project
Development of a novel “manufacturing system-level quality and productivity optimizer tool” enabling the evaluation of the system level impacts of the defect avoidance policies that can be adopted within single processes.
Research project
The activity carried out, as part of the CUP B98I24002620009 project, is characterized by two services aimed at improving skills, methods and tools applied to Process Engineering and Information Systems for Knowledge Management (KM) and GoToMarket).
Research project
Obiettivo generale del progetto TECNOMED-HUB è quello di realizzare, sul territorio piemontese, una piattaforma tecnologica a supporto della ricerca medica 4.0, basata sull’integrazione delle piattaforme multi-omiche già presenti (ma facilmente implementabili ad altre tecnologie in futuro), con algoritmi di autoapprendimento, data mining e big data analytics.