Innovation Impact in the Textile Industry: From the Toyota Production System to Artificial Intelligence
Sustainability,
Год журнала:
2025,
Номер
17(3), С. 1170 - 1170
Опубликована: Янв. 31, 2025
The
Toyota
Production
System
(TPS)
was
a
revolutionary
approach
to
automobile
production
that
influenced
companies
all
over
the
world.
fight
against
redundancy
is
at
core
of
this
approach.
textile
industry
remains
one
most
polluting
sectors
worldwide,
which
makes
environmental
sustainability
key
concern.
In
line
with
national
priorities,
are
striving
balance
profitability
sustainability,
minimizing
defects
and
reducing
waste.
This
study
explores
evolution
systems
from
TPS
principles
integration
Artificial
Intelligence
(AI)
how
they
can
be
used
perspective.
Smartex,
start-up
recognized
as
winner
Web
Summit
2021
competition,
chosen
focus
case
study.
Employing
qualitative
research
methods,
including
content
analysis
interviews,
management
reports
website
data,
examines
parallels
distinctions
between
Smartex’s
AI-driven
system.
findings
highlight
Smartex
revolutionizing
by
leveraging
AI
avoid
reduce
waste,
advancing
both
commercial
objectives.
Finally,
implications
limitations
explained.
Язык: Английский
Smart factory technologies and their transformative implications: a Blavaan and Bayesian SEM
Total Quality Management & Business Excellence,
Год журнала:
2025,
Номер
unknown, С. 1 - 24
Опубликована: Фев. 13, 2025
Concepts
like
robotic
systems,
the
Internet
of
Things,
3D
printing,
and
artificial
intelligence
collectively
known
as
smart
systems
have
revolutionized
manufacturing
fronts.
This
research
focuses
on
how
staggered
implementations
these
technologies
affect
two
vital
elements
manufacturing:
quality
technological
advancement.
The
implications
effects
are
analysed
by
Blavaan
Bayesian
SEM
approaches
in
study.
Based
surveying
33
industrial
experts,
four
questions
formulated,
which
were
focused
production
speed,
resource
utilization,
labour
costs,
transformation,
results
show
that
factory
innovative
enhance
productivity
efficiency
production.
IoT
sensors
inspection
dimensional
reliability
material
quality,
invention
cycles,
AI
designs.
Язык: Английский
Knowledge-Based Adaptive Design of Experiments (KADoE) for Grinding Process Optimization Using an Expert System in the Context of Industry 4.0
Journal of Manufacturing and Materials Processing,
Год журнала:
2025,
Номер
9(2), С. 62 - 62
Опубликована: Фев. 17, 2025
The
integration
of
human–cyber–physical
systems
(HCPSs),
IoT,
digital
twins,
and
big
data
analytics
underpins
Industry
4.0,
transforming
traditional
manufacturing
into
smart
with
capabilities
for
real-time
monitoring,
quality
assessment,
anomaly
detection.
A
key
advancement
is
the
transition
from
static
to
adaptive
design
experiments
(DoE),
using
iterative
refinement.
This
paper
introduces
an
innovative
DoE
embedded
in
expert
system
grinding,
combining
data-driven
knowledge-based
methodologies.
KSF
Grinding
Expert™
recommends
optimized
grinding
control
variables,
guided
by
a
multi-objective
optimization
framework
Non-dominated
Sorting
Genetic
Algorithm
II
(NSGA-II)
Gray
Relational
Analysis
(GRA).
rule-based
iteratively
refines
recommendations
through
feedback
historical
insights,
reducing
number
trials
excluding
suboptimal
parameters.
case
study
validates
approach,
demonstrating
significant
enhancements
process
efficiency
precision.
strategy
reduces
experimental
trials,
adapts
according
different
processes,
can
prevent
critical
defects
such
as
surface
cracks.
In
study,
results
which
are
offered
validated
over
90%
accuracy
incorporated
system’s
knowledge
base,
enabling
continuous
improvement
reduced
experimentation
future
iterations.
Язык: Английский
Surface treatment techniques and control methods for enhancing corrosion resistance and very thin films management in fast nuclear reactors
Results in Surfaces and Interfaces,
Год журнала:
2025,
Номер
unknown, С. 100468 - 100468
Опубликована: Фев. 1, 2025
Язык: Английский
Exploring the import of mechatronics engineering in medicine: a review
Beni-Suef University Journal of Basic and Applied Sciences,
Год журнала:
2025,
Номер
14(1)
Опубликована: Март 23, 2025
Abstract
Background
The
interdisciplinary
nature
of
mechatronics
has
spurred
huge
progress
in
medicine
to
facilitate
the
creation
robotic
surgery,
wearable
health
monitoring,
and
bio-inspired
robots.
All
these
technologies
enhance
precision
boost
diagnostic
capability,
enable
real-time
patient
monitoring.
For
example,
robotic-assisted
surgeries
have
recorded
a
50%
cut
complications
40%
reduction
healing
times,
while
technology
enhanced
early
anomaly
detection
by
80%,
saving
emergency
hospitalisation.
Main
body
This
review
critically
examines
evolution
applications
focusing
on
problems
including
financial
burdens,
confidentiality
data,
compliance
with
regulation.
Emphasis
is
placed
heavily
regulatory
approval
processes
required
organisations
such
as
US
Food
Drug
Administration
(FDA)
International
Organisation
for
Standardisation
(ISO)
that
typically
delay
use
life-saving
equipment
3–5
years.
In
addition,
expensive
price
surgery
systems
(~$2
million
per
unit)
extensive
training
(20–40
procedures
be
proficient)
are
inhibiting
factors.
New
trends
robots
nanomedicine
also
considered
here,
which
exhibited
fantastic
potential
minimally
invasive
therapy,
nanorobot-based
cancer
therapies
tumour
growth
inhibition
limiting
systemic
side
effects.
Conclusions
To
propel
ethical
sustainable
adoption
healthcare,
this
proposed
development
partnerships
among
engineers,
clinicians,
policymakers,
simplifies
clearance
processes,
designs
low-cost,
scalable
products.
Through
avenues,
can
proceed
revolutionise
enhancing
outcomes
expanding
accessibility
cutting-edge
medical
technology.
Язык: Английский
Design, Modeling, and Experimental Validation of a Hybrid Piezoelectric–Magnetoelectric Energy-Harvesting System for Vehicle Suspensions
World Electric Vehicle Journal,
Год журнала:
2025,
Номер
16(4), С. 237 - 237
Опубликована: Апрель 18, 2025
The
growing
demand
for
sustainable
and
self-powered
technologies
in
automotive
applications
has
led
to
increased
interest
energy
harvesting
from
vehicle
suspensions.
Recovering
mechanical
road-induced
vibrations
offers
a
viable
solution
powering
wireless
sensors
autonomous
electronic
systems,
reducing
dependence
on
external
power
sources.
This
study
presents
the
design,
modeling,
experimental
validation
of
hybrid
energy-harvesting
system
that
integrates
piezoelectric
magnetoelectric
effects
efficiently
convert
into
electrical
energy.
A
model-based
systems
engineering
(MBSE)
approach
was
used
optimize
architecture,
ensuring
high
conversion
efficiency,
durability,
seamless
integration
suspension
systems.
theoretical
modeling
both
mechanisms
developed,
providing
analytical
expressions
harvested
as
function
parameters.
designed
then
fabricated
tested
under
controlled
excitations
validate
models.
Experimental
results
demonstrate
achieves
maximum
output
16
µW/cm2
effect
3.5
effect.
strong
correlation
between
predictions
measurements
confirms
feasibility
this
applications.
Язык: Английский
Acoustic-Based Machine Main State Monitoring for High-Speed CNC Drilling
Machines,
Год журнала:
2025,
Номер
13(5), С. 372 - 372
Опубликована: Апрель 29, 2025
This
paper
introduces
an
acoustic-based
monitoring
system
for
high-speed
CNC
drilling,
aimed
at
optimizing
processes
and
enabling
real-time
machine
state
detection.
High-fidelity
acoustic
sensors
capture
sound
signals
during
drilling
operations,
allowing
the
identification
of
critical
events
such
as
tool
engagement,
material
breakthrough,
withdrawal.
Advanced
signal
processing
techniques,
including
spectrogram
analysis
Fast
Fourier
Transform,
extract
dominant
frequencies
patterns,
while
learning
algorithms
like
DBSCAN
clustering
classify
operational
states
cutting,
returning.
Experimental
studies
on
materials
acrylic,
PTFE,
hardwood
reveal
distinct
profiles
influenced
by
properties
conditions.
Smoother
patterns
lower
characterize
PTFE
whereas
produces
higher
rougher
due
to
its
density
resistance.
These
findings
demonstrate
correlation
between
emissions
machining
dynamics,
non-invasive
predictive
maintenance.
As
AI
power
increases,
it
is
expected
in-situ
process
information
achieve
resolution,
enhancing
precision
in
data
interpretation
decision-making.
A
key
contribution
this
project
creation
open
library
processes,
fostering
collaboration
innovation
intelligent
manufacturing.
By
integrating
big
concepts
algorithms,
supports
continuous
monitoring,
anomaly
detection,
optimization.
AI-ready
hardware
enhances
accuracy
efficiency
improving
quality,
reducing
wear,
minimizing
downtime.
The
research
establishes
a
transformative
approach
advancing
manufacturing
systems.
Язык: Английский
Computer-Vision-Based Product Quality Inspection and Novel Counting System
Applied System Innovation,
Год журнала:
2024,
Номер
7(6), С. 127 - 127
Опубликована: Дек. 18, 2024
In
this
study,
we
aimed
to
enhance
the
accuracy
of
product
quality
inspection
and
counting
in
manufacturing
process
by
integrating
image
processing
human
body
detection
algorithms.
We
employed
SIFT
algorithm
combined
with
traditional
comparison
metrics
such
as
SSIM,
PSNR,
MSE
develop
a
defect
system
that
is
robust
against
variations
rotation
scale.
Additionally,
YOLOv8
Pose
was
used
detect
correct
errors
caused
interference
on
load
cell
real
time.
By
applying
differencing
technique,
accurately
calculated
unit
weight
products
determined
their
total
count.
our
experiments
conducted
weighing
over
1
kg,
achieved
high
99.268%.
The
integration
algorithms
load-cell-based
demonstrates
reliable
real-time
automated
environments.
Язык: Английский