Recent Advances and Challenges in Industrial Robotics: A Systematic Review of Technological Trends and Emerging Applications
Processes,
Год журнала:
2025,
Номер
13(3), С. 832 - 832
Опубликована: Март 12, 2025
Industrial
robotics
has
shifted
from
rigid,
task-specific
tools
to
adaptive,
intelligent
systems
powered
by
artificial
intelligence
(AI),
machine
learning
(ML),
and
sensor
integration,
revolutionizing
efficiency
human–robot
collaboration
across
manufacturing,
healthcare,
logistics,
agriculture.
Collaborative
robots
(cobots)
slash
assembly
times
30%
boost
quality
15%,
while
reinforcement
enhances
autonomy,
cutting
errors
energy
use
20%.
Yet,
this
review
transcends
descriptive
summaries,
critically
synthesizing
these
trends
expose
unresolved
tensions
in
scalability,
cost,
societal
impact.
High
implementation
costs
legacy
system
incompatibilities
hinder
adoption,
particularly
for
SMEs,
interoperability
gaps—despite
frameworks,
like
OPC
UA—stifle
multi-vendor
ecosystems.
Ethical
challenges,
including
workforce
displacement
cybersecurity
risks,
further
complicate
progress,
underscoring
a
fragmented
field
where
innovation
outpaces
practical
integration.
Drawing
on
systematic
of
high-impact
literature,
study
uniquely
bridges
technological
advancements
with
interdisciplinary
applications,
revealing
disparities
economic
feasibility
equitable
access.
It
critiques
the
literature’s
isolation
trends—cobots’
safety,
ML’s
perception’s
precision—proposing
following
cohesive
research
directions:
cost-effective
modularity,
standardized
protocols,
ethical
frameworks.
By
prioritizing
interoperability,
sustainability,
paper
charts
path
evolve
inclusively,
offering
actionable
insights
researchers,
practitioners,
policymakers
navigating
dynamic
landscape.
Язык: Английский
Implementation of a Sustainable Framework for Process Optimization Through the Integration of Robotic Process Automation and Big Data in the Evolution of Industry 4.0
Processes,
Год журнала:
2025,
Номер
13(2), С. 536 - 536
Опубликована: Фев. 14, 2025
This
study
explores
the
integration
of
Robotic
Process
Automation
(RPA)
and
Big
Data
within
a
sustainable
framework
for
process
optimization
in
context
Industry
4.0.
As
industries
strive
to
enhance
operational
efficiency
while
maintaining
sustainability,
need
innovative
solutions
has
become
crucial.
The
research
applies
PICO
methodology
(Population,
Intervention,
Comparison,
Outcome)
assess
impact
combining
these
technologies
on
sustainability.
Through
real-world
case
study,
demonstrates
that
RPA
significantly
reduces
execution
times,
minimizes
errors,
promotes
business
practices.
results
show
combined
not
only
enhances
but
also
contributes
lower
economic,
environmental,
social
impacts.
findings
validate
hypotheses,
proving
proposed
fosters
balance
between
technological
advancement
provides
valuable
insights
into
potential
4.0
drive
both
corporate
responsibility,
offering
novel
approach
seeking
embrace
digital
transformation
achieving
long-term
growing
body
knowledge
synergy
RPA,
Data,
sustainability
industrial
contexts.
Язык: Английский