A Smart Factory Architecture Based on Industry 4.0 Technologies: Open-Source Software Implementation
IEEE Access,
Год журнала:
2023,
Номер
11, С. 101727 - 101749
Опубликована: Янв. 1, 2023
The
Smart
Factory
has
been
a
concept
studied
during
the
last
decade
that
not
standardized
yet;
for
this
reason,
academy
and
industry
have
developed
wide
variety
of
new
architectures
describe
integration
elements
digitization
interconnection.
present
research
aims
to
introduce
architecture
proposal
migrating
traditional
(automation)
smart
(digitization)
factories,
implemented
through
open-source
software.
proposed
is
integrated,
first
time,
by
interconnection
six
main
elements:
cyber-physical
systems,
edge
computing,
artificial
intelligence,
cloud
data
analytics,
cybersecurity;
describes
in
detail
their
definitions,
sub-elements,
between
elements,
minimum
requirements
implementation.
test
factory
was
done
scale
pilot
testing
pick
place
process,
where
assembly
wood
pieces
from
geometric
Tangram's
puzzle
required;
includes
six-degree-of-freedom
robot
arm,
conveyor,
vision
system,
storage
area.
case
study
conducted
allowed
four
puzzles
(fish,
house,
rocket,
swan)
were
assembled
with
different
batches
pieces.
implementation
flexibility
adaptability.
final
reports
included
status
assembly,
number
assembled,
stored,
sequence,
time.
Similarly,
development
SCADA
system
asset
control
as
well
monitoring.
KPIs
process
measured
productivity
(OTD)
time
tracking
(ATCT
TA)
16
tests,
founding
manufacturing
cell
fully
integrated
repeatability;
SF
represents
an
alternative
small
medium
automated
factories
achieve
digitization,
it
ready
be
tested
more
complex
scenario.
Язык: Английский
IoT Real-Time Production Monitoring and Automated Process Transformation in Smart Manufacturing
Journal of Organizational and End User Computing,
Год журнала:
2024,
Номер
36(1), С. 1 - 25
Опубликована: Янв. 17, 2024
Conventional
automobile
manufacturing
plants
involve
intricate
assembly,
testing,
and
debugging
processes
heavily
reliant
on
manual
operations.
This
study
aims
to
explore
the
application
of
industrial
internet
things
(IIoT)
deep
learning
algorithms
achieve
process
automation
in
manufacturing.
Firstly,
utilizing
IIoT
technology,
OPC
UA,
point
cloud
fitting
techniques,
a
comprehensive
modeling
most
equipment
materials
within
factory
is
conducted,
constructing
digital
twin
(DT)
model
as
virtual
representation
actual
equipment.
Subsequently,
innovatively
introduces
Q
network
algorithm,
facilitating
automatic
transition
production
improving
efficiency.
Through
comparison
with
ten
baseline
models,
proposed
demonstrates
an
improvement
efficiency
at
least
four
percentage
points
compared
other
models.
Experimental
validation
confirms
effectiveness
smart
for
electric
vehicle
Язык: Английский
A Brief Review on Flexible Electronics for IoT: Solutions for Sustainability and New Perspectives for Designers
Sensors,
Год журнала:
2023,
Номер
23(11), С. 5264 - 5264
Опубликована: Июнь 1, 2023
The
Internet
of
Things
(IoT)
is
gaining
more
and
popularity
it
establishing
itself
in
all
areas,
from
industry
to
everyday
life.
Given
its
pervasiveness
considering
the
problems
that
afflict
today's
world,
must
be
carefully
monitored
addressed
guarantee
a
future
for
new
generations,
sustainability
technological
solutions
focal
point
activities
researchers
field.
Many
these
are
based
on
flexible,
printed
or
wearable
electronics.
choice
materials
therefore
becomes
fundamental,
just
as
crucial
provide
necessary
power
supply
green
way.
In
this
paper
we
want
analyze
state
art
flexible
electronics
IoT,
paying
particular
attention
issue
sustainability.
Furthermore,
considerations
will
made
how
skills
required
designers
such
circuits,
features
design
tools
characterization
electronic
circuits
changing.
Язык: Английский
From Smart Devices to Smarter Systems: The Evolution of Artificial Intelligence of Things (AIoT) with Characteristics, Architecture, Use Cases and Challenges
Springer eBooks,
Год журнала:
2023,
Номер
unknown, С. 1 - 28
Опубликована: Янв. 1, 2023
Язык: Английский
Introducing an improved rime algorithm combined with gate current unit as an innovative stability monitoring and controlling model for flexible biogas-to-hydrogen/methanol system
Renewable Energy,
Год журнала:
2025,
Номер
unknown, С. 123032 - 123032
Опубликована: Апрель 1, 2025
Язык: Английский
A Review: Image Processing Techniques’ Roles towards Energy-Efficient and Secure IoT
Applied Sciences,
Год журнала:
2023,
Номер
13(4), С. 2098 - 2098
Опубликована: Фев. 6, 2023
The
goal
of
this
review
paper
is
to
highlight
the
image
processing
techniques’
role
in
Internet
Things
(IoT),
aiming
attain
an
energy-efficient
and
secure
IoT.
IoT-dependent
systems
(IoTSs)
cause
heavy
usage
energy.
This
one
biggest
issues
associated
with
IoTSs.
Another
issue
that
security
digital
content
a
big
challenge
difficulty.
Image
has
recently
played
essential
resolving
these
difficulties.
Several
researchers
have
made
efforts
improve
future
IoTSs,
which
are
summarized
article.
Day-by-day,
proposed
methods
developed,
thus
IoT
deployment
been
plainly
engaged
our
everyday
activities.
efficient
image-processing
techniques
can
be
utilized
by
IoTSs
overcome
such
proposed.
aims
those
make
contributions
direction.
Thus,
study
numerous
research
studies
on
subject.
looks
at
36
publications
relevant
several
types
innovative
work
provide
readers
map
suitable
used
certain
(i.e.,
scenarios).
Both
methodology
analysis
come
out
suggested
mind
highlighting
number
solutions
techniques)
help
design
energy-efficient,
secure,
intelligent
system.
We
some
conclusions
projections
for
work.
Язык: Английский
A new hybrid learning control system for robots based on spiking neural networks
Neural Networks,
Год журнала:
2024,
Номер
180, С. 106656 - 106656
Опубликована: Авг. 23, 2024
This
paper
presents
a
new
hybrid
learning
and
control
method
that
can
tune
their
parameters
based
on
reinforcement
learning.
In
the
proposed
method,
nonlinear
controllers
are
considered
multi-input
multi-output
functions
then
replaced
with
SNNs
algorithms.
Dopamine-modulated
spike-timing-dependent
plasticity
(STDP)
is
used
for
manipulating
synaptic
weights
between
input
output
of
neuronal
groups
(for
parameter
adjustment).
Details
presented
some
case
studies
done
such
as
Fractional
Order
PID
(FOPID)
Feedback
Linearization.
The
structure
dynamic
equations
presented,
algorithm
tested
robots
results
compared
other
works.
Moreover,
to
demonstrate
effectiveness
SNNFOPID,
we
conducted
rigorous
testing
variety
systems
including
two-wheel
mobile
robot,
double
inverted
pendulum,
four-link
manipulator
robot.
revealed
impressively
low
errors
0.01
m,
0.03
rad,
rad
each
system,
respectively.
another
controller
named
Linearization,
which
provides
acceptable
results.
Results
show
has
better
performance
in
terms
Integral
Absolute
Error
(IAE)
highly
useful
hardware
implementation
due
its
energy
consumption,
high
speed,
accuracy.
duration
necessary
achieving
full
stable
proficiency
various
robotic
using
SNNFOPD,
SNNFL
an
Asus
Core
i5
system
within
Simulink's
Simscape
environment
follows:
-
Two-link
robot
SNNFOPID:
19.85656
hours
SNNFL:
0.45828
Double
pendulum
3.455
Mobile
3.71948
Four-link
16.6789
hours.
be
generalized
like
robots.
Язык: Английский
Optimization and design of electromechanical control automation based on dual motor control algorithm
Frontiers in Mechanical Engineering,
Год журнала:
2024,
Номер
10
Опубликована: Дек. 6, 2024
Introduction
In
response
to
the
high
demand
for
dynamic
characteristics
and
control
in
current
electromechanical
automatic
systems.
Methods
This
study
first
analyzes
dual
motor
system.
A
novel
automation
model
based
on
a
algorithm
is
proposed
through
strategy
of
backlash
elimination
digital
proportional
integral
derivative
algorithm.
Results
Discussion
The
results
indicated
that
optimization
had
promoting
effect
performance
Compared
with
other
popular
models
same
type,
research
method
was
best.
During
no-load
start-up
phase,
maximum
tracking
error
synchronization
speed
new
showed
significant
decreasing
trend,
between
two
motors
being
only
0.02%.
Under
steady-state
sudden
load,
could
reach
stable
state
within
3
s,
errors
±5%.
Conclusion
summary,
combining
can
provide
theoretical
basis
practical
guidance
designing
implementing
efficient
Язык: Английский
Improved Path Tracking Control in Mobile Robots Using a Hybrid FOPID Controller with Backstepping Technique: An Experimental Study
Journal Européen des Systèmes Automatisés,
Год журнала:
2023,
Номер
56(2), С. 173 - 186
Опубликована: Апрель 30, 2023
This
study
aims
to
address
the
challenge
of
low-cost
hardware
implementation
a
combined
backstepping
with
fractional
order
PID
(FOPID)
controller
for
mobile
robots
in
real-time
applications.Moreover,
this
work
proposes
self-designed
robot
prototype
that
is
easy
realize,
low
cost,
spares
time,
and
reduces
human
effort.This
platform
was
equipped
two
DC
motors
quadratic
encoders
passive
wheels,
controlled
by
an
Arduino
mega,
where
software
code
developed
Matlab-Simulink
environment,
using
Simulink
support
package
Arduino.Four
case
studies
were
conducted
demonstrate
effectiveness
suggested
methodology.Experimental
results
improved
trajectory
tracking
performance
less
error
smooth
control
efforts,
capable
handling
trajectories
continuous
non-continuous
gradients.
Язык: Английский
A New Hybrid Learning Control System for Robots Based on Spiking Neural Networks
Опубликована: Янв. 1, 2023
This
paper
presents
a
new
hybrid
learning
and
control
method
that
can
tune
their
parameters
based
on
reinforcement
learning.
In
the
proposed
method,
nonlinear
controllers
are
considered
multi-input
multi-output
functions
then
replaced
with
SNNs
algorithms.
Dopamine-modulated
spike-timing-dependent
plasticity
(STDP)
is
used
for
manipulating
synaptic
weights
between
input
output
of
neuronal
groups
(for
parameter
adjustment).
Details
presented
some
case
studies
done
such
as
Fractional
Order
PID
(FOPID)
Feedback
Linearization.
The
structure
dynamic
equations
presented,
algorithm
tested
robots
results
compared
other
works.
addition,
to
verify
applicability
it
another
controller
named
Linearization,
which
provides
acceptable
results.
Results
show
has
better
performance
in
terms
Integral
Absolute
Error
(IAE)
highly
useful
hardware
implementation
due
its
low
energy
consumption,
high
speed,
accuracy.
be
generalized
systems
like
robots.
Язык: Английский