Exploring the Challenges of Integrating Lean Green Practices in Industry 4.0 Manufacturing Frameworks: An Empirical Study
Springer series in advanced manufacturing,
Год журнала:
2024,
Номер
unknown, С. 277 - 292
Опубликована: Янв. 1, 2024
Язык: Английский
Strategic Design Optimization of Cutting Tools for Enhanced Manufacturing Efficiency
Springer series in advanced manufacturing,
Год журнала:
2024,
Номер
unknown, С. 251 - 276
Опубликована: Янв. 1, 2024
Язык: Английский
Comparative analysis of response surface methodology and adaptive neuro-fuzzy inference system for predictive fault detection and optimization in beverage industry
Frontiers in Mechanical Engineering,
Год журнала:
2024,
Номер
10
Опубликована: Окт. 7, 2024
Maintenance
is
crucial
for
ensuring
equipment
reliability
and
minimizing
downtime
while
managing
associated
costs.
This
study
investigates
a
data-driven
approach
to
predicting
machine
faults
using
Response
Surface
Methodology
(RSM)
Adaptive
Neuro-Fuzzy
Inference
System
(ANFIS).
RSM
was
employed
develop
mathematical
model
analyze
how
operational
parameters
such
as
pressure,
voltage,
current,
vibration,
temperature
affect
fault
occurrence.
Data
were
collected
at
three
levels
each
parameter
central
composite
design.
The
identified
that
peaked
pressure
of
28.38
N/m
2
,
an
operating
voltage
431.77
V,
current
consumption
12.54
A,
vibration
47.17
Hz,
25°C,
with
maximum
25
observed.
Conversely,
the
lowest
detection
occurred
29.42
441.04
12.04
49.46
46.5°C.
A
strong
correlation
found
between
these
faults,
achieving
high
accuracy
(R
=
98.22%)
statistical
significance
(
p
-value
<0.05),
demonstrating
its
in
faults.
also
compared
ANFIS
process
optimization
beverage
industry.
While
effectively
optimized
relationships,
ANFIS,
adaptive
learning
capabilities,
provided
superior
prediction
accuracy.
comparative
analysis
highlighted
strengths
both
methods
suggested
integrating
them
could
enhance
predictive
maintenance
strategies.
findings
offer
valuable
insights
industry
practitioners,
recommending
combined
improve
detection,
optimize
production
processes,
efficiency.
Язык: Английский
Behavior of CuO as solid lubricant inside ZTA matrices
AIP Advances,
Год журнала:
2024,
Номер
14(8)
Опубликована: Авг. 1, 2024
This
investigation
delves
into
the
behavior
of
copper
oxide
(CuO)
as
a
solid
lubricant
inside
zirconia
toughened
alumina
(ZTA)
ceramic
composites.
The
starts
with
preparation
ZTA
through
co-precipitation
followed
by
powder
metallurgy
to
develop
CuO
(1.5
wt.
%)/ZTA
In
all
cases,
hot
isotactic
pressing
is
applied
for
densification.
fully
densified
samples
are
thoroughly
mirror-polished
investigate
mechanical
and
tribological
properties.
A
1.8%
reduction
in
micro-hardness
6%
improvement
fracture
toughness
observed
incorporation
matrices.
analysis
reveals
that
presence
ionic
at
grain
boundary
leads
formation
copper-rich
phases,
causing
decrease
hardness.
However,
softer
particles
contribute
crack
bridging
deflection,
enhancing
toughness.
Subsequent
properties
highlights
positive
influence
phases
acting
secondary
component
within
matrix.
significant
enhancement
39.34%
Coefficient
Friction
(COF)
achieved
incorporating
can
be
attributed
patchy
layer
smearing
squeezing
actions
on
wear
debris
during
sliding.
uniform
results
smoother
more
polished
surfaces,
leading
an
both
COF
specific
rate.
Further
various
phenomena
contributing
surface
wear,
including
pullout
particles,
micro-fracture,
high
abrasions,
laminar
removal
grains.
Overall,
introduction
proves
beneficial,
showcasing
improved
developed
composites,
application
dies,
inserts,
sparkplugs,
etc.
Язык: Английский