Smart Cities,
Год журнала:
2024,
Номер
7(6), С. 3458 - 3488
Опубликована: Ноя. 12, 2024
This
paper
presents
a
comprehensive
review
of
the
transformative
impacts
3D
printing
technology
on
smart
cities.
As
cities
face
rapid
urbanization,
resource
shortages,
and
environmental
degradation,
innovative
solutions
such
as
additive
manufacturing
(AM)
offer
potential
pathways
for
sustainable
urban
development.
By
synthesizing
66
publications
from
2015
to
2024,
study
examines
how
improves
infrastructure,
enhances
sustainability,
fosters
community
engagement
in
city
planning.
Key
benefits
include
reducing
construction
time
material
waste,
lowering
costs,
enabling
creation
scalable,
affordable
housing
solutions.
The
also
addresses
emerging
areas
integration
with
digital
twins
(DTs),
machine
learning
(ML),
AI
optimize
infrastructure
predictive
maintenance.
It
highlights
use
materials
soft
robotics
structural
health
monitoring
(SHM)
repairs.
Despite
promising
advancements,
challenges
remain
terms
cost,
scalability,
need
interdisciplinary
collaboration
among
engineers,
designers,
planners,
policymakers.
findings
suggest
roadmap
future
research
practical
applications
cities,
contributing
ongoing
discourse
technologically
advanced
Internet of Things and Cyber-Physical Systems,
Год журнала:
2023,
Номер
3, С. 192 - 204
Опубликована: Янв. 1, 2023
The
Internet
of
Things
(IoT)
is
playing
a
significant
role
in
the
transformation
traditional
factories
into
smart
Industry
4.0
by
using
network
interconnected
devices,
sensors,
and
software
to
monitor
optimize
production
process.
Predictive
maintenance
IoT
can
also
be
used
prevent
machine
failures,
reduce
downtime,
extend
lifespan
equipment.
To
energy
usage
during
part
manufacturing,
manufacturers
obtain
real-time
insights
consumption
patterns
deploying
sensors
factories.
Also,
provide
more
comprehensive
view
factory
environment
enhance
workplace
safety
identifying
potential
hazards
alerting
workers
dangers.
Suppliers
use
IoT-enabled
tracking
devices
shipments
updates
on
delivery
times
locations
order
analyze
supply
chain
Moreover,
powerful
technology
which
inventory
management
costs,
improve
efficiency,
visibility
levels
movements.
impact
internet
thing
industry
4.0,
review
presented.
Applications
things
such
as
predictive
maintenance,
asset
tracking,
management,
quality
control,
process
monitoring,
efficiency
optimization
are
reviewed.
Thus,
analyzing
application
new
ideas
advanced
methodologies
provided
control
processes.
Sensors International,
Год журнала:
2021,
Номер
2, С. 100110 - 100110
Опубликована: Янв. 1, 2021
Sensors
play
a
crucial
role
in
factory
automation
making
the
system
intellectual.
Different
types
of
sensors
are
available
as
per
suitability
and
applications;
some
them
produced
mass
market
at
affordable
costs.
The
standard
sensor
position
sensors,
pressure
flow
temperature
force
sensors.
They
used
many
sectors,
such
motorsport,
medical,
industry,
aerospace,
agriculture,
daily
life.
objective
Industry
4.0
is
to
increase
efficiency
through
automation.
vital
components
4.0,
allowing
several
transitions
changes
positions,
length,
height,
external
dislocations
industrial
production
facilities
be
detected,
measured,
analysed,
processed.
Smart
factories
will
also
enhance
sustainability
by
tracking
real-time
output,
automated
control
systems
minimise
potential
maintenance
It
can
seen
that
digitalisation
improve
mobility,
which
gives
advanced
manufacturing
firms
competitive
advantage.
This
paper
discusses
their
various
types,
along
with
significant
capabilities
for
manufacturing.
step-by-step
working
Blocks
Quality
Services
during
implementation
elaborated
diagrammatically.
Finally,
we
identified
thirteen
applications
4.0.
provides
an
excellent
opportunity
development
across
globe.
In
enjoy
higher
acceptance
rates
benefit
from
fully
enabled
connecting
data
exchange
logistics
integration.
coming
years,
installations
may
grow
process
management,
lines,
digital
supply
chains.
Applied Sciences,
Год журнала:
2022,
Номер
12(16), С. 8081 - 8081
Опубликована: Авг. 12, 2022
In
the
era
of
fourth
industrial
revolution,
several
concepts
have
arisen
in
parallel
with
this
new
such
as
predictive
maintenance,
which
today
plays
a
key
role
sustainable
manufacturing
and
production
systems
by
introducing
digital
version
machine
maintenance.
The
data
extracted
from
processes
increased
exponentially
due
to
proliferation
sensing
technologies.
Even
if
Maintenance
4.0
faces
organizational,
financial,
or
even
source
repair
challenges,
it
remains
strong
point
for
companies
that
use
it.
Indeed,
allows
minimizing
downtime
associated
costs,
maximizing
life
cycle
machine,
improving
quality
cadence
production.
This
approach
is
generally
characterized
very
precise
workflow,
starting
project
understanding
collection
ending
decision-making
phase.
paper
presents
an
exhaustive
literature
review
methods
applied
tools
intelligent
maintenance
models
Industry
identifying
categorizing
projects
challenges
encountered,
type
maintenance:
condition-based
(CBM),
prognostics
health
management
(PHM),
remaining
useful
(RUL).
Finally,
novel
workflow
presented
including
decision
support
phase
wherein
recommendation
platform
presented.
ensures
fluid
communication
between
equipment
throughout
their
context
smart
Applied Sciences,
Год журнала:
2024,
Номер
14(2), С. 898 - 898
Опубликована: Янв. 20, 2024
Predictive
maintenance
(PdM)
is
a
policy
applying
data
and
analytics
to
predict
when
one
of
the
components
in
real
system
has
been
destroyed,
some
anomalies
appear
so
that
can
be
performed
before
breakdown
takes
place.
Using
cutting-edge
technologies
like
artificial
intelligence
(AI)
enhances
performance
accuracy
predictive
systems
increases
their
autonomy
adaptability
complex
dynamic
working
environments.
This
paper
reviews
recent
developments
AI-based
PdM,
focusing
on
key
components,
trustworthiness,
future
trends.
The
state-of-the-art
(SOTA)
techniques,
challenges,
opportunities
associated
with
PdM
are
first
analyzed.
integration
AI
into
real-world
applications,
human–robot
interaction,
ethical
issues
emerging
from
using
AI,
testing
validation
abilities
developed
policies
later
discussed.
study
exhibits
potential
areas
for
research,
such
as
digital
twin,
metaverse,
generative
collaborative
robots
(cobots),
blockchain
technology,
trustworthy
Industrial
Internet
Things
(IIoT),
utilizing
comprehensive
survey
current
SOTA
opportunities,
challenges
allied
PdM.
Sensors,
Год журнала:
2023,
Номер
23(8), С. 4131 - 4131
Опубликована: Апрель 20, 2023
This
paper
proposes
the
use
of
AHP-Gaussian
method
to
support
selection
a
smart
sensor
installation
for
an
electric
motor
used
in
escalator
subway
station.
The
methodology
utilizes
Analytic
Hierarchy
Process
(AHP)
framework
and
is
highlighted
its
ability
save
decision
maker's
cognitive
effort
assigning
weights
criteria.
Seven
criteria
were
defined
selection:
temperature
range,
vibration
weight,
communication
distance,
maximum
power,
data
traffic
speed,
acquisition
cost.
Four
sensors
considered
as
alternatives.
results
analysis
showed
that
most
appropriate
was
ABB
Ability
sensor,
which
scored
highest
analysis.
In
addition,
this
could
detect
any
abnormalities
equipment's
operation,
enabling
timely
maintenance
preventing
potential
failures.
proposed
proved
be
effective
approach
selecting
selected
reliable,
accurate,
cost-effective,
contributing
safe
efficient
operation
equipment.
