Smart manufacturing
The project addresses the problem of managing the data collected when servicing very different objects in order to optimize their costs and availability for the end user. This will be done by developing algorithms that enable intelligent information management in order to simulate scenarios, reduce time to data availability and to optimize maintenance.
To manage the data collected when servicing very different objects is achieved by developing algorithms that enable intelligent information management in order to simulate scenarios, reduce time to data availability and to optimize maintenance.
For the aeronautics sector, the aim of the project is to create an iterative simulation model that integrates all the information described in order to predict landing plans and logistic and strategic indications, integrated with the planning of depot activities.
For the railway sector, the project intends to develop new enabling technologies and methodologies (based on service-oriented architecture (SOA) and human-machine interface (HMI) architecture) for operators directly involved in maintenance by developing tools based on non-traditional interaction approaches through the introduction of visual information systems support (augmented reality, reverse engineering) for remote assistance of railway vehicles and optoelectronic measurement systems for railway infrastructure.
For the space sector, the aim is to develop a system to highlight the alarms and checklist orders suggested to the operator by the anomaly identified or by the level of recentness (and therefore the necessary attention required) for the specific behaviour found.
EnginSoft is the lead partner for the project’s first objective, dedicated to the Maintenace Planner module’s development. The purpose is to create an algorithm to generate a landing plan (Removal Plan) and a Maintenance Planner (MP) that can be applied to a fleet of aircraft engines to maximize their availability to end users and minimize the time and cost of routine and/or extraordinary maintenance work.
EnginSoft has a primary role both in coordinating the objective and in developing the algorithms and the iterative simulation model to predict the service status of a fleet of aircraft engines.
DTA - DISTRETTO TECNOLOGICO AEROSPAZIALE, BLACKSHAPE, EKA, ENGINSOFT SPA, GE AVIO SRL, MERMEC, PLANETEK ITALIA, POLITECNICO DI BARI, POLITECNICO DI TORINO, UNIVERSITÀ DEL SALENTO
Funding Scheme MIUR Programma Operativo Nazionale (PON) “Ricerca e Innovazione 2014-2020” | Call identifier Avviso MIUR n. 1735 del 13/07/2017
30 months
September 2018 - February 2021
Distretto Tecnologico Aerospaziale (DTA) scarl
Alessandro Mellone
10
Some of our competences in research and technology transfer
Research project
The overall objective of the TECNOMED-HUB project is to create, in the Piedmont region of Italy, a technology platform to support medical research 4.0, based on the integration of existing multi-omics platforms with self-learning algorithms, data mining, and big data analytics.
