TY - GEN
T1 - NDE In-Process for Metal Parts Fabricated Using Powder Based Additive Manufacturing
AU - Bond, Leonard J.
AU - Koester, Lucas W.
AU - Taheri, Hossein
N1 - Publisher Copyright:
© 2019 SPIE.
PY - 2019/3/18
Y1 - 2019/3/18
N2 - Ensuring adequate quality for additive manufactured (AM) materials presents unique metrology challenges to the on-line process measurement and nondestructive evaluation (NDE) communities. AM parts now have complex forms that are not possible using subtractive manufacturing and there are moves for their use in safety criticality components. This paper briefly reviews the status, challenges and metrology opportunities throughout the AM process from powder to finished parts. The primary focus is on new acoustic signatures that have been demonstrated to correlate process parameters with on-line measurement for monitoring and characterization during the build. In-process, quantitative characterization and monitoring of material state is anticipated to be potentially transformational in advancing adoption of metal AM parts, including offering the potential for early part rejection, part condition guided process control or even potentially in-process repair. This approach will enable more effective deployment of quality assessment metrology into the layer-by-layer material build with designed morphology. In this proof-of-concept study acoustic-based process monitoring signals were collected during the Direct Energy Deposition (DED) AM process with different process conditions to investigate and determine if variations in process conditions can be discriminated. A novel application of signal processing tools is used for the identification and use of metrics based on temporal and spectral features in acoustic signals for the purpose of in-situ monitoring and characterization of conditions in an AM process. Results show that the features identified in signatures are correlated with the process conditions and can be used for classifying different states in the process.Ensuring adequate quality for additive manufactured (AM) materials presents unique metrology challenges to the on-line process measurement and nondestructive evaluation (NDE) communities. AM parts now have complex forms that are not possible using subtractive manufacturing and there are moves for their use in safety criticality components. This paper briefly reviews the status, challenges and metrology opportunities throughout the AM process from powder to finished parts. The primary focus is on new acoustic signatures that have been demonstrated to correlate process parameters with on-line measurement for monitoring and characterization during the build. In-process, quantitative characterization and monitoring of material state is anticipated to be potentially transformational in advancing adoption of metal AM parts, including offering the potential for early part rejection, part condition guided process control or even potentially in-process repair. This approach will enable more effective deployment of quality assessment metrology into the layer-by-layer material build with designed morphology. In this proof-of-concept study acoustic-based process monitoring signals were collected during the Direct Energy Deposition (DED) AM process with different process conditions to investigate and determine if variations in process conditions can be discriminated. A novel application of signal processing tools is used for the identification and use of metrics based on temporal and spectral features in acoustic signals for the purpose of in-situ monitoring and characterization of conditions in an AM process. Results show that the features identified in signatures are correlated with the process conditions and can be used for classifying different states in the process.
AB - Ensuring adequate quality for additive manufactured (AM) materials presents unique metrology challenges to the on-line process measurement and nondestructive evaluation (NDE) communities. AM parts now have complex forms that are not possible using subtractive manufacturing and there are moves for their use in safety criticality components. This paper briefly reviews the status, challenges and metrology opportunities throughout the AM process from powder to finished parts. The primary focus is on new acoustic signatures that have been demonstrated to correlate process parameters with on-line measurement for monitoring and characterization during the build. In-process, quantitative characterization and monitoring of material state is anticipated to be potentially transformational in advancing adoption of metal AM parts, including offering the potential for early part rejection, part condition guided process control or even potentially in-process repair. This approach will enable more effective deployment of quality assessment metrology into the layer-by-layer material build with designed morphology. In this proof-of-concept study acoustic-based process monitoring signals were collected during the Direct Energy Deposition (DED) AM process with different process conditions to investigate and determine if variations in process conditions can be discriminated. A novel application of signal processing tools is used for the identification and use of metrics based on temporal and spectral features in acoustic signals for the purpose of in-situ monitoring and characterization of conditions in an AM process. Results show that the features identified in signatures are correlated with the process conditions and can be used for classifying different states in the process.Ensuring adequate quality for additive manufactured (AM) materials presents unique metrology challenges to the on-line process measurement and nondestructive evaluation (NDE) communities. AM parts now have complex forms that are not possible using subtractive manufacturing and there are moves for their use in safety criticality components. This paper briefly reviews the status, challenges and metrology opportunities throughout the AM process from powder to finished parts. The primary focus is on new acoustic signatures that have been demonstrated to correlate process parameters with on-line measurement for monitoring and characterization during the build. In-process, quantitative characterization and monitoring of material state is anticipated to be potentially transformational in advancing adoption of metal AM parts, including offering the potential for early part rejection, part condition guided process control or even potentially in-process repair. This approach will enable more effective deployment of quality assessment metrology into the layer-by-layer material build with designed morphology. In this proof-of-concept study acoustic-based process monitoring signals were collected during the Direct Energy Deposition (DED) AM process with different process conditions to investigate and determine if variations in process conditions can be discriminated. A novel application of signal processing tools is used for the identification and use of metrics based on temporal and spectral features in acoustic signals for the purpose of in-situ monitoring and characterization of conditions in an AM process. Results show that the features identified in signatures are correlated with the process conditions and can be used for classifying different states in the process.
KW - NDE
KW - acoustic signatures
KW - additive manufacturing
KW - in-process monitoring
KW - process condition.
UR - https://digitalcommons.georgiasouthern.edu/manufact-eng-facpubs/77
UR - https://www.spiedigitallibrary.org/conference-proceedings-of-spie/10973/2520611/NDE-in-process-for-metal-parts-fabricated-using-powder-based/10.1117/12.2520611.short?SSO=1
U2 - 10.1117/12.2520611
DO - 10.1117/12.2520611
M3 - Conference article
AN - SCOPUS:85069671543
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Smart Structures and NDE for Energy Systems and Industry 4.0
A2 - Meyendorf, Norbert G.
A2 - Gath, Kerrie
A2 - Niezrecki, Christopher
PB - SPIE
T2 - Smart Structures and NDE for Energy Systems and Industry 4.0 2019
Y2 - 4 March 2019 through 5 March 2019
ER -