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MAShES

Multimodal spectrAl control of laSer processing with cognitivE abilities

Total Cost €

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EC-Contrib. €

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Partnership

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 MAShES project word cloud

Explore the words cloud of the MAShES project. It provides you a very rough idea of what is the project "MAShES" about.

deal    thirdly    firstly    efficient    learning    spot    play    snapshot    standardisation    melt    welding    representative    size    networked    modulation    mwir    monitoring    texture    emissivity    metal    diagnosis    will    loop    demonstration    estimation    multimodal    compact    quality    multispectral    acquired    image    pool    act    time    secondly    profile    scenarios    powder    temperature    mashes    regarding    modular    independent    validation    grey    adjustment    modalities    techniques    gas    imaging    variables    seam    easily    accurate    unified    bodies    contributions    cognitive    machine    usability    deposition    vis    rt    3d    facilities    factory    operation    physical    regard    laser    proposes    breakthrough    designed    dynamic    dissimilar    spectral    dynamics    manufacturing    envisaged    compliance    geometry    multiple    flow    solution    cyber    inputs    outputs    brings    resolved    2d    simultaneously    data    closed    materials    power    interoperability    surface    self    observation    combines    prototypes    customizable    lmd    speed   

Project "MAShES" data sheet

The following table provides information about the project.

Coordinator
ASOCIACION DE INVESTIGACION METALURGICA DEL NOROESTE 

Organization address
address: CALLE RELVA TORNEIROS 27A
city: PORRINO
postcode: 36410
website: www.aimen.es

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Spain [ES]
 Project website http://www.mashesproject.eu
 Total cost 3˙673˙157 €
 EC max contribution 3˙673˙157 € (100%)
 Programme 1. H2020-EU.2.1.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies - Information and Communication Technologies (ICT))
2. H2020-EU.2.1.5.1. (Technologies for Factories of the Future)
 Code Call H2020-FoF-2014
 Funding Scheme RIA
 Starting year 2014
 Duration (year-month-day) from 2014-12-01   to  2017-11-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    ASOCIACION DE INVESTIGACION METALURGICA DEL NOROESTE ES (PORRINO) coordinator 509˙375.00
2    FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V. DE (MUNCHEN) participant 490˙125.00
3    CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS FR (PARIS) participant 476˙938.00
4    PRIMA ELECTRO SPA IT (MONCALIERI) participant 440˙875.00
5    PANEPISTIMIO PATRON EL (RIO PATRAS) participant 306˙250.00
6    OFFICE NATIONAL D'ETUDES ET DE RECHERCHES AEROSPATIALES FR (PALAISEAU) participant 280˙406.00
7    Sill Optics GmbH & Co. KG DE (Wendelstein) participant 250˙250.00
8    NEW INFRARED TECHNOLOGIES SL ES (MADRID) participant 238˙250.00
9    PERMANOVA LASERSYSTEM AKTIEBOLAG SE (MOLNDAL) participant 226˙063.00
10    CENTRO RICERCHE FIAT SCPA IT (ORBASSANO) participant 201˙000.00
11    EMO-ORODJARNA DOO SI (CELJE) participant 195˙625.00
12    BITADDICT AB SE (GRABO) participant 58˙000.00

Map

 Project objective

MAShES proposes a breakthrough approach to image-based laser processing closed-loop control.

Firstly, a compact, snapshot, and multispectral imaging system in the VIS/MWIR spectral range will be developed. This approach will enable a multimodal process observation that combines different imaging modalities. Moreover, it will enable an accurate estimation of temperature spatially resolved and independent on emissivity values, even for non-grey bodies and dissimilar materials. Secondly, a fully embedded approach to real time (RT) control will be adopted for efficient processing of acquired data and high speed -multiple inputs/ multiple outputs- closed-loop control. Thirdly, a cognitive control system based on the use of machine learning techniques applied to process quality diagnosis and self-adjustment of the RT control will be developed.

As a result, a unified and compact embedded solution for RT-control and high speed monitoring will be developed that brings into play: - The accurate measurement of temperature distribution, - The 3D seam profile and 2D melt pool geometry, - The surface texture dynamics, and process speed.

MAShES control will act simultaneously on multiple process variables, including laser power and modulation, process speed, powder and gas flow, and spot size.

MAShES will deal with usability and interoperability issues for compliance with cyber-physical operation of the system in a networked and cognitive factory. Moreover, standardisation issues will be addressed regarding the processes and the control system and contributions in this regard are envisaged.

MAShES will be designed under a modular approach, easily customizable for different laser processing applications in highly dynamic manufacturing scenarios. Validation and demonstration of prototypes of MAShES system will be done for laser welding and laser metal deposition (LMD) in operational scenarios at representative end-user facilities.

 Deliverables

List of deliverables.
Communication material and record reports Websites, patent fillings, videos etc. 2019-03-06 10:29:58
Demonstration of the MAShES system for Laser Metal Deposition- LMD processes Documents, reports 2019-01-09 15:27:35
Demonstration of the MAShES system for laser welding applications Documents, reports 2019-01-09 15:27:35
MAShES prototype Demonstrators, pilots, prototypes 2019-01-09 15:27:35
MAShES dataset for benchmarking Open Research Data Pilot 2019-03-06 09:58:58
Project Website Websites, patent fillings, videos etc. 2019-02-12 12:36:18

Take a look to the deliverables list in detail:  detailed list of MAShES deliverables.

 Publications

year authors and title journal last update
List of publications.
2017 Jean Luc Pellouard
Optical Nano-resonators and infrared applications at MiNaO
published pages: , ISSN: , DOI:
2019-05-27
2017 Alexios Papacharalampopoulos, Panagiotis Stavropoulos, John Stavridis
Adaptive control of thermal processes: laser welding and additive manufacturing paradigms
published pages: , ISSN: 2212-8271, DOI:
Procedia CIRP 2019-05-27
2016 Alexios Papacharalampopoulos, John Stavridis, Panagiotis Stavropoulos, George Chryssolouris
Cloud-based Control of Thermal Based Manufacturing Processes
published pages: 254-259, ISSN: 2212-8271, DOI: 10.1016/j.procir.2016.09.036
Procedia CIRP 55 2019-05-27
2018 John Stavridis, Alexios Papacharalampopoulos, Panagiotis Stavropoulos
Quality assessment in laser welding: a critical review
published pages: 1825-1847, ISSN: 0268-3768, DOI: 10.1007/s00170-017-0461-4
The International Journal of Advanced Manufacturing Technology 94/5-8 2019-05-27
2018 John Stavridis, Alexios Papacharalampopoulos, Panagiotis Stavropoulos
A cognitive approach for quality assessment in laser welding
published pages: , ISSN: , DOI:
2019-05-27
2017 Anton Garcia-Diaz, Veronica Panadeiro, Baltasar Lodeiro, Jorge Rodriguez-Araujo, Alexios Papacharalampopoulos, Panagiotis Stavropoulos, John Stavridis
OpenLMD, an open source middleware and toolkit for laser-based additive manufacturing of large metal parts
published pages: , ISSN: 0736-5845, DOI:
Robotics and Computer Integrated Manufacturing 2019-05-27
2017 Verónica Panadeiro-Castro, Jorge Rodriguez-Araújo, Antón García-Díaz, Germán Vergara
OpenLMD, MWIR imaging for high speed control for LMD processing
published pages: , ISSN: 0898-1507, DOI:
Lasers in Engineering 2019-05-27
2017 Adrian Pallas, Anton Garcia-Diaz, Veronica Panadeiro
A modular approach to online monitoring for laser-based 3D printing using deep MWIR features
published pages: , ISSN: 0956-5515, DOI:
Journal of Intelligent manufacturing 2019-05-27

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The information about "MASHES" are provided by the European Opendata Portal: CORDIS opendata.

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