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ASTM Selected Technical Papers
Progress in Additive Manufacturing 2020
By
Nima Shamsaei
Nima Shamsaei
Symposium Chair and STP Editor
1
Auburn University
,
Auburn, AL,
US
Search for other works by this author on:
Mohsen Seifi
Mohsen Seifi
Symposium Chair and STP Editor
2
ASTM International
,
Washington, DC,
US
Search for other works by this author on:
ISBN:
978-0-8031-7721-5
No. of Pages:
432
Publisher:
ASTM International
Publication date:
2022

Additive manufacturing enables novel classes of product complexity together with high levels of customization for functional components that shall meet strict quality requirements. Because of this, novel product qualification and statistical process control challenges must be faced in the industry. Traditional methods could become not applicable in this new scenario as they are based on monitoring simple geometrical or dimensional features, and they entail a training phase consisting of several copies of the same part. Because of this, the possibility of using data and signals acquired via in situ sensors during the process to support qualification procedures has been attracting a great deal of industrial interest. This study presents an in situ metrology method that combines in situ geometry reconstruction of the part via layerwise image segmentation and a quality modeling approach that allows estimating synthetic geometric patterns in terms of one-dimensional profile data. The method is specifically designed for lattice structures, one kind of complex shape enabled by additive manufacturing processes. It aims at providing a methodological framework to anticipate geometrical assessment and anomaly detection while the part is being built and even in the presence of one-of-a-kind structures. A real case study in laser powder bed fusion is presented to demonstrate the feasibility and benefits of the proposed approach.

1.
Colosimo
B. M.
and
Grasso
M.
, “
On-Machine Measurement, Monitoring and Control
,” in
Precision Metal Additive Manufacturing
, ed.
Leach
R.
and
Carmignato
S.
(
Boca Raton, FL
:
CRC Press
,
2020
), 346–390.
2.
Grasso
M.
and
Colosimo
B. M.
, “
Process Defects and In-situ Monitoring Methods in Metal Powder Bed Fusion: A Review
,”
Measurement Science and Technology
28
,
no. 4
(
2017
): 1–25.
3.
Everton
S. K.
,
Hirsch
M.
,
Stravroulakis
P.
,
Leach
R. K.
, and
Clare
A. T.
, “
Review of In-Situ Process Monitoring and In-Situ Metrology for Metal Additive Manufacturing
,”
Materials and Design
95
(
2016
): 431–445.
4.
Aminzadeh
M.
, “
A Machine Vision System for In-Situ Quality Inspection in Metal Powder-Bed Additive Manufacturing
” (PhD dissertation,
Georgia Institute of Technology
,
2016
).
5.
Aminzadeh
M.
and
Kurfess
T.
, “
Vision-Based Inspection System for Dimensional Accuracy in Powder-Bed Additive Manufacturing
,” (paper presentation, ASME 2016 11th International Manufacturing Science and Engineering Conference,
Blacksburg, VA
, June 27–July 1,
2016
).
6.
zur Jacobsmühlen
J.
,
Achterhold
J.
,
Kleszczynski
S.
,
Witt
G.
, and
Merhof
D.
, “
In Situ Measurement of Part Geometries in Layer Images from Laser Beam Melting Processes
,”
Progress in Additive Manufacturing
4
,
no. 2
(
2019
): 155–165.
7.
Gobert
C.
,
Reutzel
E. W.
,
Petrich
J.
,
Nassar
A. R.
, and
Phoha
S.
, “
Application of Supervised Machine Learning for Defect Detection during Metallic Powder Bed Fusion Additive Manufacturing Using High Resolution Imaging
,”
Additive Manufacturing
21
(
2018
): 517–528.
8.
Gaikwad
A.
,
Imani
F.
,
Rao
P.
,
Yang
H.
, and
Reutzel
E.
, “
Design Rules and In-Situ Quality Monitoring of Thin-Wall Features Made Using Laser Powder Bed Fusion
,” in
Proceedings of the ASME 14th International Manufacturing Science and Engineering Conference
, vol.
1
(
New York
:
American Society of Mechanical Engineers
,
2019
),
9.
Caltanissetta
F.
,
Grasso
M.
,
Petro
S.
, and
Colosimo
B. M.
, “
Characterization of In-Situ Measurements Based on Layerwise Imaging in Laser Powder Bed Fusion
,”
Additive Manufacturing
24
(
2018
): 183–199.
10.
He
P.
,
Zhong
K.
,
Liu
X.
,
Zhou
G.
,
Wang
C.
,
Wei
Q.
,
Shi
Y.
, and
Li
Z.
, “
A Phase-Guided Method for Extracting the Contour of the Fusion Area in Laser Powder Bed Fusion
,” in
Proceedings Volume 11205, Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019)
(
Bellingham, WA
:
International Society for Optics and Photonics
, 2019),
11.
Pagani
L.
,
Grasso
M.
,
Scott
P. J.
, and
Colosimo
B. M.
, “
Automated Layerwise Detection of Geometrical Distortions in Laser Powder Bed Fusion
,”
Additive Manufacturing
36
(
2020
):
12.
Wu
X.
,
Su
Y.
, and
Shi
J.
, “
Perspective of Additive Manufacturing for Metamaterials Development
,”
Smart Materials and Structures
28
,
no. 9
(
2019
),
13.
Colosimo
B. M.
,
Grasso
M.
,
Garghetti
F.
, and
Rossi
B.
, “
Complex Geometries in Additive Manufacturing: A New Solution for Lattice Structure Modeling and Monitoring
,” Journal of Quality Technology (
2021
):
14.
Grasso
M. L.
G.
,
Remani
A.
,
Dickins
A.
,
Colosimo
B. M.
, and
Leach
R. K.
, “
In-Situ Measurement and Monitoring Methods for Metal Powder Bed Fusion—An Updated Review
,”
Measurement Science and Technology
32
,
no. 11
(
2021
): 112001.
15.
Foster
B. K.
,
Reutzel
E. W.
,
Nassar
A. R.
,
Hall
B. T.
,
Brown
S. W.
, and
Dickman
C. J.
, “
Optical, Layerwise Monitoring of Powder Bed Fusion
,” in
Proceedings of the 26th Annual Solid Freeform Fabrication Symposium
(
Austin, TX
:
University of Texas
,
2015
), 295–307.
16.
Soomro
S.
,
Munir
A.
, and
Choi
K. N.
, “
Hybrid Two-Stage Active Contour Method with Region and Edge Information for Intensity Inhomogeneous Image Segmentation
,”
PLoS ONE
13
,
no. 1
(
2018
):
17.
Liu
S.
and
Peng
Y.
, “
A Local Region-Based Chan-Vese Model for Image Segmentation
,”
Pattern Recognition
45
,
no. 7
(
2012
): 2769–2779.
18.
Osher
S.
and
Fedkiw
R.
,
Level Set Methods and Dynamic Implicit Surfaces
(
New York
:
Springer
,
2003
).
19.
Ramsay
J. O.
and
Silverman
B. W.
,
Applied Functional Data Analysis: Methods and Case Studies
(
New York, NY
:
Springer
,
2002
).
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