Datasets:
akumar33
/
manufacturing

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objects O
with O
complex O
geometrical O
shapes O
directly O
from O
a O
digital O
model S-CONPRI
. O
However O
, O
achieving O
the O
full O
potential O
of O
AM S-MANP
is O
hampered O
by O
many O
challenges O
, O
including O
the O
lack O
of O
predictive B-CONPRI
models E-CONPRI
that O
correlate O
processing O
parameters S-CONPRI
with O
the O
properties S-CONPRI
of O
the O
processed S-CONPRI
part O
. O
We O
develop O
a O
Gaussian S-CONPRI
process-based O
predictive B-CONPRI
model E-CONPRI
for O
the O
learning O
and O
prediction S-CONPRI
of O
the O
porosity S-PRO
in O
metallic B-MACEQ
parts E-MACEQ
produced O
using O
selective B-MANP
laser I-MANP
melting E-MANP
( O
SLM S-MANP
– O
a O
laser-based O
AM B-MANP
process E-MANP
) O
. O
More O
specifically O
, O
a O
spatial O
Gaussian S-CONPRI
process O
regression B-CONPRI
model E-CONPRI
is O
first O
developed O
to O
model S-CONPRI
part O
porosity S-PRO
as S-MATE
a O
function O