Material Knowledge for Robust Additive Manufacturing
Transcript of Material Knowledge for Robust Additive Manufacturing
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PROJECT POSSIBILITIES AND AVAILABLE EQUIPMENT
CIAM Pilot Project MeetingStavanger
September 2016
Amin S. Azar1, Olav Åsebø2 ,Erik Andreassen1
1SINTEF Materials and Chemistry, Oslo2SINTEF Raufoss Manufacturing, Trondheim
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SINTEF Raufoss Manufacturing ASSINTEF VentureSINTEF NBLSINTEF NordSINTEF Business DevelopmentSINTEF BrasilMoLab
AM core activities in SINTEF
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AM Project portfolio
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Metal PrintingProsess
CubitalSolider 5600
3D systemsSLA-250
Prod
uctio
n Fa
cilit
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Concept Laser
Facts:1814 metal AM machines were sold in the whole world by 2015.
Source: Wohlers Assocoiates, Inc.
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Powder based machines in Norway (2016)
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Tronrud Engineering ASEOSINT M280 from EOS250 mm x 250 mm x 325 mmCold building chamberGass atmosphere0.4 kW laser
NTNU GjøvikA2X from Arcam200 mm x 200 mm x 380 mmWarm building chamberVacuum atmosphere3 kW Electron Beam
Promet ASSLM 280 HL from SLM solutions280 mm x 280 mm x 350 mmWarm building chamberGass atmosphere0.4 kW laser
NTNU TrondheimM2 Cusing from ConceptLaser250 mm x 250 mm x 280 mmCold building chamberGass atmosphere0.2 kW laser
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Different technologiesGains and losses
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Expe
rimen
tatio
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Design and Modelling
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End of part IFeel free to ask questions!
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Part IIKPN-MKRAM project and detailed
description of the facilities
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AM is a key enabling technology
Complex geometries (e.g. conformal cooling channels)
Lightweight designs (e.g. by topology optimisation and lattice structures)
Individual variation at (almost) no additional cost
"Game changer" for materials technology
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Additive manufacturing – Challenges
■There are several challenges for AM technology, as highlighted in roadmaps andreports:
■ The cost per part is still high compared to traditional processes (but AM should not beconsidered as a "replacement" process).
■ Today, AM based production includes many manual operations, in particular post-processing.
■ Engineers lack knowledge about the AM technologies and how to utilize their advantages.
■ There is no current database of properties of "AM materials" for production use.
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■Regarding the mechanical performance of AM parts, the main challenges are related to:
■ limited knowledge about the effective material properties.
o process-microstructure-property relationships, including anisotropy, defects and inhomogeneity.
■Part-to-part consistency.
■Machine-to-machine variation.
■Material-to-material variation.
■Availability of materials.
Additive manufacturing – Challenges
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Building AM competence for the Norwegian manufacturing industry
■BIA-KPN MKRAM (2015-2019) "Material Knowledge for Robust Additive Manufacturing"
■ In-depth investigations of specific AM materials and processes to achieve robust and predictable material properties for industrial AM
■Participants:
■GKN Aerospace Norway, Kongsberg Automotive, Nammo Raufoss, OM BE Plast, Sandvik Teeness
■SINTEF, NTNU/Gjøvik, NTNU
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BIA-KPN project (2015-2019) Material Knowledge for Robust Additive Manufacturing
■ Focus on powder bed fusion processes and materials that are in progress of industrial implementation:
■ Metals: Maraging tool steel Stainless steel Ni-base super alloy (Inconel)
■ Polymers: Polyamides Reinforced polyamides
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BIA-KPN project (2015-2019)Material Knowledge for Robust Additive Manufacturing
• Powder bed fusion as a process in an industrial manufacturing cycle
■Material properties may e.g. be affected by:
■ Differences between powder batches
■ Storage and handling of powder
■ Exposure to repeated process cycles, – sifting & rinsing of powder…
■ Environmental conditions
■ Processing parameters
■ Part orientation in the build chamber
MKRAM: Investigate these effects and develop best-practice guidelines
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BIA-KPN Project (2015-2019) Material Knowledge for Robust Additive Manufacturing
■ "Effective" material properties of components made by AM, including repeatability
■ "Materials science" approach:
Process → microstructure → mechanical performance
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BIA-KPN project (2015-2019)Material Knowledge for Robust Additive Manufacturing
■Microstructure, mechanical performance, NDE and post-processing
■Mechanical testing (test specimens and real parts)
■Characterization of microstructures and defects Including NDE methods.
■Effect of post-processing operations, e.g.■ Blasting, machining and polishing of critical surfaces■ Annealing – reduction of residual stresses■ Various treatments to manipulate the microstructure and mechanical
properties
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CT instruments at NTNU/SINTEF and partner in Austria
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BIA-KPN Project (2015-2019) Material Knowledge for Robust Additive Manufacturing
AM Material Densification Process Development
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■Material models for FEA , also with failure criteria
■For fatigue crack growth in metals we will explore afracture mechanics concept modelling the additionalcontribution to the crack driving force by materialinhomogeneity.
■Such models can be used to optimize "buildorientation" and layer thickness, and establish designrules for part features in critical applications.
BIA-KPN Project (2015-2019) Material Knowledge for Robust Additive Manufacturing
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Summary:■ Establish a "materials technology basis" for selected AM materials and processes■ Establish practical guidelines, e.g. for reducing part-to-part variation
BIA-KPN Project (2015-2019) Material Knowledge for Robust Additive Manufacturing
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End of part IIFeel free to ask questions!
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Teknologi for et bedre samfunn