A path to follow to overcome foundational barriers to the adoption of artificial intelligence within the manufacturing industry: a conceptual framework
Enterprise Information Systems,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 5, 2025
Язык: Английский
MedicalGLM: A Pediatric Medical Question Answering Model with a quality evaluation mechanism
Journal of Biomedical Informatics,
Год журнала:
2025,
Номер
unknown, С. 104793 - 104793
Опубликована: Март 1, 2025
Язык: Английский
A large language model-enabled machining process knowledge graph construction method for intelligent process planning
Advanced Engineering Informatics,
Год журнала:
2025,
Номер
65, С. 103244 - 103244
Опубликована: Март 8, 2025
Язык: Английский
A Review on Integrating IoT, IIoT, and Industry 4.0: A Pathway to Smart Manufacturing and Digital Transformation
IET Information Security,
Год журнала:
2025,
Номер
2025(1)
Опубликована: Янв. 1, 2025
The
industrial
Internet
of
Things
(IIoT)
has
become
an
innovative
technology
that
brought
many
benefits
to
industries
and
organizations.
This
review
presents
a
comprehensive
analysis
IIoT’s
applications,
highlighting
its
ability
optimize
operations
through
advanced
connectivity,
real‐time
data
exchange,
automation,
importance
in
the
context
Industry
4.0.
Emphasizing
distinction
between
IIoT
traditional
IoT,
paper
explores
how
focuses
on
enhancing
ecosystems
integrating
cyber‐physical
systems
(CPSs).
article
explains
establish
highly
linked
infrastructure
support
cutting‐edge
services
ensure
greater
flexibility
efficiency.
It
emphasizes
role
CPS
automation
control
(IACSs)
realizing
potential
IIoT.
Security
concerns,
important
part
IIoT,
are
addressed
conversations
protecting
networked
systems,
assuring
operational
reliability,
emphasizing
need
for
strong
security
measures
prevent
threats
vulnerabilities.
Furthermore,
critical
technologies
such
as
machine
learning
(ML),
artificial
intelligence
(AI),
various
communication
protocols,
including
fifth
generation
(5G)
message
queuing
telemetry
transport
(MQTT),
investigated
their
improve
system
performance
decision‐making
processes.
In
addition,
also
discusses
safety
precautions
challenges
using
Finally,
addressing
issues
promoting
successful
adoption
achieving
expected
benefits.
study
offers
valuable
resources
researchers,
academics,
decision‐makers
implement
environments.
Язык: Английский
Interpretable knowledge recommendation for intelligent process planning with graph embedded deep reinforcement learning
Advanced Engineering Informatics,
Год журнала:
2025,
Номер
65, С. 103321 - 103321
Опубликована: Апрель 12, 2025
Язык: Английский
A Novel Autoencoder-Integrated Clustering Methodology for Inventory Classification: A Real Case Study for White Goods Industry
Sustainability,
Год журнала:
2024,
Номер
16(21), С. 9244 - 9244
Опубликована: Окт. 24, 2024
This
article
presents
an
inventory
classification
method
that
provides
more
accurate
results
in
the
white
goods
factory,
which
will
contribute
to
sustainability,
sustainability
economics,
and
supply
chain
management
targets.
A
novel
application
is
presented
with
real-world
data.
Two
different
datasets
are
used,
these
compared
each
other.
These
larger
dataset
Stock
Keeping
Unit
(SKU)-based
(6.032
SKUs),
smaller
one
product-group-based
(270
product
groups).
In
first
phase,
Artificial
Intelligence
(AI)
clustering
methods
have
not
been
used
field
of
classification,
our
knowledge,
applied
datasets;
obtained
using
K-Means,
Gaussian
mixture,
agglomerative
clustering,
spectral
methods.
second
stage,
autoencoder
separately
hybridized
AI
develop
a
approach
classification.
Fuzzy
C-Means
(FCM)
third
step
classify
inventories.
At
end
study,
nine
methodologies
(“K-Means,
clustering”
without
C-Means)
two
datasets.
It
shown
proposed
new
hybrid
gives
much
better
than
classical
Язык: Английский