{"id":7833,"date":"2023-06-19T09:49:04","date_gmt":"2023-06-19T07:49:04","guid":{"rendered":"https:\/\/sistemapolipiemonte.it\/smea-enginsoft\/"},"modified":"2025-10-22T18:38:03","modified_gmt":"2025-10-22T16:38:03","slug":"smea-enginsoft","status":"publish","type":"post","link":"https:\/\/sistemapolipiemonte.it\/en\/smea-enginsoft\/","title":{"rendered":"SMEA"},"content":{"rendered":"

Diagnostic and prognostic methodologies and development of sensors for functional integrity monitoring applied to the aeronautics and transportation sectors.<\/p>\n

 <\/p>\n

\"\" \"\"<\/p>\n

Description<\/strong><\/h3>\n

The ultimate goal of the SMEA project is the development of a shared platform of expertise and technologies for the development of functional and performance monitoring, diagnostics and prognostics models, with particular reference to aeronautical applications relating to the propulsion system and the structural integrity of components, and thus for the design, development and integration of methodologies, sensor systems and microsystems.<\/p>\n

Result to be enhanced<\/h3>\n

Development of a Digital Twin system for diagnostic and prognostic monitoring applied to a component designed and manufactured using additive technology, which integrates innovative and effective multi-scale modelling systems, sensor systems and methodologies for diagnostic and prognostic prediction of the functional and structural integrity of aeronautical components made of advanced materials, and in particular manufactured using innovative production processes (additive manufacturing).
\nIn addition, a further result was achieved with the application of innovative sensor systems to monitor anomalies in aircraft engines, such as gear box vibrations, combustion instability, and contamination of lubricant fluids.<\/p>\n

Why is it importat?<\/strong><\/h3>\n

The project enabled the development of a Methodology for Structural Health Monitoring (SHM) of components made by additive manufacturing with the following advanced elements
\na. Procedure for the design of components made by additive manufacturing with implementation of a semi-automatic procedure for optimal sensor positioning.
\nb. Development of meta-models able to process the data from the sensors and return the stress state and residual fatigue life of the components.
\nc. Development of a GUI for the (quasi) real-time evaluation of the mechanical performance of the component made by additive manufacturing.
\nThrough a Digital Twin approach for Prognostics Health Monitoring (PHM) purposes, it is possible to detect abnormal behaviour of the monitored systems, which could lead to unexpected failures during service by increasing the ability of early diagnostics (failure detection). Monitoring allows better planning of maintenance interventions, being able to evaluate intervention costs and residual efficiency of the system during service. Likewise, it is possible to create a different business model for service activities to be proposed to the customer, replacing and repairing systems only when this is actually necessary. Finally, it is possible to create a data history, which will make it possible to adapt operating models and interpret different failure modes and related maintenance.<\/p>\n

Acknowledgements to the project partners supported by MIUR Notice no. 713\/Ric. of 29\/10\/2010 Title III – \u2018Creation of new Districts and\/or Public-Private Aggregations: DTA SCARL – Distretto Tecnologico Aerospaziale Pugliese (leader), University of Salento, ENGINSOFT SpA, Avio Aero, Leonardo-Finmeccanica Spa – Aircraft Division (observer), CNR – National Research Council<\/p>\n

Project and Acronym:<\/strong>\u00a0 SMEA
\nTRL:<\/strong>\u00a0 Iniziale 4 – Finale 6
\nReferece call:<\/strong> MIUR Avviso n. 713\/Ric. del 29\/10\/2010 Titolo III \u2010 “Creazione di nuovi Distretti e\/o Aggregazioni Pubblico Private”
\nInnovation Cluster to contact:<\/strong> None
\nTechnologies used:<\/strong> IoT, sensors, data mining, simulation, digital twin, additive manufacturing<\/p><\/div>

Lead company:<\/strong>
\nDTA SCARL – Distretto Tecnologico Aerospaziale Pugliese<\/p>\n

Collaborating company <\/b>:<\/strong>
\nEnginsoft S.p.a
\nn.gramegna@enginsoft.com<\/a> | www.enginsoft.com<\/a><\/p><\/div><\/p>\n","protected":false},"excerpt":{"rendered":"

Diagnostic and prognostic methodologies and development of sensors for functional integrity monitoring applied to the aeronautics and transportation sectors.<\/p>\n

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