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Ricercatore a tempo determinato Legge 240/10 art.24-B

Membro Centro Interdipartimentale (IAM@PoliTo - Integrated Additive Manufacturing)

+39 0110907031 / 7031 (DAUIN)

Gruppi di ricerca EDA - Electronic Design Automation
Progetti di ricerca

Finanziati da bandi competitivi

  • Integrated framework for quality assurance of additive manufacturing, (2021-2022) - Responsabile Scientifico

    Ricerca da Enti privati e Fondazioni

    ERC sectors

    PE6_2 - Computer systems, parallel/distributed systems, sensor networks, embedded systems, cyber-physical systems PE6_1 - Computer architecture, pervasive computing, ubiquitous computing

    Abstract

    The major challenges are represented by:1. Real-time responseComputational costs of the artificial intelligence algorithms are constrained by the necessity of detecting defects on a layer-by-layer basis.To tackle this problem, we will consider software/hardware acceleration strategies.2. Need for large number of training images and datasetsML techniques are built on top of a pre-annotated training sets. This set should be:Massive ? in case of deep learning, huge amount of experimental dataBalanced ? same number of examples of different experimental conditions (faulty/not faulty, different categories of defects, different geometries of manufacts, different materials, etc.) 3. Need for heterogeneous data integrationThe algorithms need to integrate data from different sources (cameras, sensors, CAD, post-processing tests, user manuals, etc.), which may be structured (e.g. images) or unstructured (e.g. manuals) and have different formats and granularities

    Strutture interne coinvolte

  • Quality assurance for additive manufacturing, (2020-2021) - Responsabile Scientifico

    Ricerca da Enti privati e Fondazioni

    ERC sectors

    PE6_11 - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video) PE6_2 - Computer systems, parallel/distributed systems, sensor networks, embedded systems, cyber-physical systems

    SDG

    Obiettivo 12. Garantire modelli sostenibili di produzione e di consumo

    Abstract

    Ensuring quality and standardization of mechanical properties of the manufacts through implementation of robust on-line process monitoring.The project concept relies on the development and integration of state-of-the-art quality monitoring systems and artificial intelligence into the AM process, to avoid uncontrolled defects, improve process robustness,stability and repeatability.Improving AM processing time and costs To this date, AM is mainly a trial-and-error process, where most of the faulty artifacts are detected only AFTER the end of a job. This impacts on the processing time and overall costs of the process. Layer-wise detection of faults would reduce the overall processing time and costs.

    Strutture interne coinvolte

  • Image analytics for in-situ defects detection in Additive Manufacturing, (2019-2020) - Responsabile Scientifico

    Ricerca da Enti privati e Fondazioni

    Abstract

    Accordo di cooperazione CRF-Polito 2018-2022

    Paesi coinvolti

    • ITALIA

    Enti/Aziende coinvolti

    • FCA Italy S.p.A.

    Strutture interne coinvolte

  • VerSatilE plug-and-play platform enabling remote pREdictive mainteNAnce, (2017-2020) - Responsabile Scientifico

    Ricerca UE - H2020 - Cross-cutting activities - IND

    Vedi la scheda del progetto su CORDIS

    Abstract

    The growing complexity of modern engineering systems and manufacturing processes is an obstacle to concept and implement Intelligent Manufacturing Systems (IMS) and keep these systems operating at high levels of reliability. Additionally, the number of sensors and the amount of data gathered on the factory floor constantly increases. This opens the vision of truly connected production processes where all machinery data are accessible allowing easier maintenance of them in case of unexpected events. SERENA project will build upon these needs for saving time and money, minimizing the costly production downtimes. The proposed solutions are covering the requirements for versatility, transferability, remote monitoring and control by a) a plug-and-play cloud based communication platform for managing the data and data processing remotely, b) advanced IoT system and smart devices for data collection and monitoring of machinery conditions, c) artificial intelligence methods for predictive maintenance (data analytics, machine learning) and planning of maintenance and production activities, d) AR based technologies for supporting the human operator for maintenance activities and monitoring of the production machinery status. SERENA represents a powerful platform to aid manufacturers in easing their maintenance burdens and for this purpose will be applied in different applications. More specifically, SERENA project will focus on advancing the TRL of the existing developments into levels TRL5 to TRL7. For this purpose, SERENA consortium will fully demonstrate the proposed approach in different industrial areas (white goods, metrological engineering and elevators production) and investigate applicability in steel parts production industry (extended-demonstration activities) checking the link to other industries (automotive, aerospace etc.) showing the versatile character of the project.

    Paesi coinvolti

    • Finlandia
    • Germania
    • Spagna
    • Italia
    • Paesi Bassi
    • Eire
    • Grecia

    Enti/Aziende coinvolti

    • TEKNOLOGIAN TUTKIMUSKESKUS VTT OY
    • FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.
    • TRIMEK SA
    • WHIRLPOOL EMEA SPA
    • OCULAVIS GMBH
    • VDL WEWELER BV
    • POLITECNICO DI TORINO
    • FINN-POWER OY
    • EMC INFORMATION SYSTEMS INTERNATIONAL
    • SYNAREA CONSULTANTS SRL
    • ENGINEERING - INGEGNERIA INFORMATICA SPA
    • PANEPISTIMIO PATRON
    • KONE INDUSTRIAL OY

    Strutture interne coinvolte

Finanziati da contratti commerciali

  • Realizzazione di algoritmo per la stima dello Stato di Salute delle batterie Li-ione, con particolare riferimento alle applicazioni a bordo veicolo, (2022-2023) - Responsabile Scientifico

    Ricerca Commerciale

    Paesi coinvolti

    • ITALIA

    Enti/Aziende coinvolti

    • EDISON S.p.A.

    Strutture interne coinvolte