International Journal of Engineering Continuity,
Journal Year:
2022,
Volume and Issue:
2(1), P. 40 - 48
Published: March 3, 2022
With
the
development
of
intelligent
manufacturing,
whether
from
consideration
capacity,
efficiency,
or
convenience,
requirements
for
mobile
robots
are
increasing,
reasonable
regional
path
planning
is
one
most
critical
needs,
and
a
genetic
algorithm
best
way
to
solve
this
problem,
but
in
some
complex
working
environments,
traditional
algorithms
will
cause
problems,
such
as
not
smooth,
steering
angle
too
large,
number
turns
etc.
In
paper,
an
improved
utilized
optimize
path-planning
problem
circumvent
common
issues
arising
other
approaches.
The
Improved
Genetic
Algorithm
(IGA)
has
emerged
significant
advancement
field
optimization
techniques.
By
incorporating
adaptive
features,
refined
approach
yields
enhanced
performance
accuracy
when
compared
algorithms.
Building
on
foundational
principles
evolutionary
computation,
IGA
employs
innovative
strategies,
crossover
mutation
operators,
navigate
solution
spaces
effectively.
It
can
also
reduce
computation
time
increase
efficiency
by
considering
various
considerations,
environmental
constraints
avoiding
obstacle.
Applied Sciences,
Journal Year:
2023,
Volume and Issue:
13(22), P. 12374 - 12374
Published: Nov. 15, 2023
Time
series
prediction
stands
at
the
forefront
of
fourth
industrial
revolution
(Industry
4.0),
offering
a
crucial
analytical
tool
for
vast
data
streams
generated
by
modern
processes.
This
literature
review
systematically
consolidates
existing
research
on
predictive
analysis
time
within
framework
Industry
4.0,
illustrating
its
critical
role
in
enhancing
operational
foresight
and
strategic
planning.
Tracing
evolution
from
first
to
revolution,
paper
delineates
how
each
phase
has
incrementally
set
stage
today’s
data-centric
manufacturing
paradigms.
It
critically
examines
emergent
technologies
such
as
Internet
things
(IoT),
artificial
intelligence
(AI),
cloud
computing,
big
analytics
converge
context
4.0
transform
into
actionable
insights.
Specifically,
explores
applications
maintenance,
production
optimization,
sales
forecasting,
anomaly
detection,
underscoring
transformative
impact
accurate
forecasting
operations.
The
culminates
call
action
dissemination
management
these
technologies,
proposing
pathway
leveraging
drive
societal
economic
advancement.
Serving
foundational
compendium,
this
article
aims
inform
guide
ongoing
practice
intersection
4.0.
Robotics and Computer-Integrated Manufacturing,
Journal Year:
2024,
Volume and Issue:
89, P. 102766 - 102766
Published: March 20, 2024
Disassembly
is
a
decisive
step
in
the
remanufacturing
process
of
End-of-Life
(EoL)
products.
As
an
emerging
semi-automatic
disassembly
paradigm,
human–robot
collaborative
(HRCD)
offers
multiple
methods
to
enhance
flexibility
and
efficiency.
However,
HRCD
increases
complexity
planning
determining
optimal
sequence
scheme.
Currently,
optimisation
heuristic
difficult
interpret,
results
cannot
be
guaranteed
as
globally
optimal.
Consequently,
this
paper
introduces
general
ontology
model
for
HRCD,
along
with
rule-based
reasoning
method,
automatically
generate
Firstly,
establishes
disassembly-related
information
EoL
products
standardised
approach.
Then,
customised
rules
are
proposed
regulate
precedence
constraints
optional
each
task
The
scheme
generated
by
combining
supportive
model.
Lastly,
gearbox
presented
case
study
validate
feasibility
methods.
Our
method
generates
compared
other
algorithms,
achieving
shortest
time
308
units
fewest
number
direction
change
3
times.
Additionally,
procedure
can
easily
tracked
modified.
both
universal
reproducible,
allowing
it
extended
support
entire
process.
Advances in logistics, operations, and management science book series,
Journal Year:
2024,
Volume and Issue:
unknown, P. 342 - 405
Published: Jan. 19, 2024
The
advent
of
Industry
4.0,
characterized
by
the
integration
digital
technologies
into
industrial
processes,
has
ushered
in
a
transformative
era
for
manufacturing
and
beyond.
This
chapter
delves
future
trends
research
directions
that
will
shape
landscape
4.0
coming
years.
One
prominent
trend
is
continued
proliferation
internet
things
(IoT)
its
convergence
with
artificial
intelligence
(AI).
As
IoT
devices
become
more
interconnected
intelligent,
they
enable
real-time
data
analysis,
predictive
maintenance,
adaptive
manufacturing,
fostering
increased
efficiency
cost-effectiveness
across
industries.
Moreover,
rise
edge
computing
set
to
redefine
processing
analytics.
deployment
powerful
resources
closer
source
promises
reduced
latency
enhanced
decision-making
capabilities,
particularly
critical
applications
like
autonomous
remote
robotics.
Sensors,
Journal Year:
2024,
Volume and Issue:
24(14), P. 4713 - 4713
Published: July 20, 2024
Robotic
Mobile
Fulfillment
Systems
(RMFSs)
face
challenges
in
handling
large-scale
orders
and
navigating
complex
environments,
frequently
encountering
a
series
of
intricate
decision-making
problems,
such
as
order
allocation,
shelf
selection,
robot
scheduling.
To
address
these
challenges,
this
paper
integrates
Deep
Reinforcement
Learning
(DRL)
technology
into
an
RMFS,
to
meet
the
needs
efficient
processing
system
stability.
This
study
focuses
on
three
key
stages
RMFSs:
allocation
sorting,
coordinated
For
each
stage,
mathematical
models
are
established
corresponding
solutions
proposed.
Unlike
traditional
methods,
DRL
is
introduced
solve
utilizing
Genetic
Algorithm
Ant
Colony
Optimization
handle
decision
making
related
orders.
Through
simulation
experiments,
performance
indicators-such
access
frequency
total
time
RMFS-are
evaluated.
The
experimental
results
demonstrate
that,
compared
our
algorithms
excel
orders,
showcasing
exceptional
superiority,
capable
completing
approximately
110
tasks
within
hour.
Future
research
should
focus
integrated
modeling
for
stage
RMFSs
designing
heuristic
further
enhance
efficiency.
