Selective disassembly sequence planning under uncertainty using trapezoidal fuzzy numbers: A novel hybrid metaheuristic algorithm
Engineering Applications of Artificial Intelligence,
Год журнала:
2023,
Номер
128, С. 107459 - 107459
Опубликована: Ноя. 22, 2023
Язык: Английский
Dynamic grouping maintenance optimization by considering the probabilistic remaining useful life prediction of multiple equipment
Eksploatacja i Niezawodnosc - Maintenance and Reliability,
Год журнала:
2024,
Номер
26(3)
Опубликована: Май 11, 2024
For
multi-equipment
maintenance
of
modern
production
equipment,
the
economic
correlation
and
degradation
uncertainty
may
lead
to
insufficient
or
excessive
maintenance,
increasing
costs.
This
paper
proposes
a
dynamic
grouping
method
based
on
probabilistic
remaining
useful
life
(RUL)
prediction
for
multiple
equipment.
Long
short
term
memory
(LSTM)
is
developed
predict
equipment
probability
RUL
by
Variational
Auto-Encoder
(VAE)
resampling.
Then,
model
constructed
minimize
cost
rate
under
known
information.
The
gazelle
optimization
algorithm
(GOA)
used
determine
optimal
time
each
To
better
verify
effectiveness
proposed
method,
numerical
case
with
six
wind
turbines
introduced
analyse
performance
GOA.
Moreover,
advantages
verified
comparing
independent
whose
reduced
10.01%.
Язык: Английский
Solving a Stochastic Multi-Objective Sequence Dependence Disassembly Sequence Planning Problem with an Innovative Bees Algorithm
Automation,
Год журнала:
2024,
Номер
5(3), С. 432 - 449
Опубликована: Авг. 23, 2024
As
the
number
of
end-of-life
products
multiplies,
issue
their
efficient
disassembly
has
become
a
critical
problem
that
urgently
needs
addressing.
The
field
sequence
planning
consequently
attracted
considerable
attention.
In
actual
process,
complex
structures
can
lead
to
significant
delays
due
interference
between
different
tasks.
Overlooking
this
result
in
inefficiencies
and
waste
resources.
Therefore,
it
is
particularly
important
study
sequence-dependent
problem.
Additionally,
activities
are
inherently
fraught
with
uncertainties,
neglecting
these
further
impact
effectiveness
disassembly.
This
first
analyze
an
uncertain
environment.
It
utilizes
stochastic
programming
approach
address
uncertainties.
Furthermore,
mixed-integer
optimization
model
constructed
minimize
time
energy
consumption
simultaneously.
Recognizing
complexity
problem,
introduces
innovative
bees
algorithm,
which
proven
its
by
showing
superior
performance
compared
other
state-of-the-art
algorithms
various
test
cases.
research
offers
solutions
for
holds
implications
advancing
sustainable
development
recycling
Язык: Английский