Predictive maintenance in oil and gas facilities, leveraging ai for asset integrity management
International Journal of Frontiers in Engineering and Technology Research,
Год журнала:
2024,
Номер
6(1), С. 016 - 026
Опубликована: Март 19, 2024
This
paper
explores
the
application
of
AI
in
predictive
maintenance
within
oil
and
gas
facilities,
discussing
its
benefits,
challenges,
future
prospects.
Through
integration
AI-driven
analytics
real-time
data
monitoring,
companies
can
enhance
their
asset
integrity
management
practices,
ultimately
driving
cost
savings
operational
excellence.
Predictive
has
become
indispensable
industry,
serving
as
a
pivotal
strategy
to
uphold
efficiency
preserve
integrity.
delves
into
profound
impact
artificial
intelligence
(AI)
technologies
on
maintenance,
ushering
new
era
proactive
equipment
management.
By
harnessing
capabilities,
preempt
failures,
curtail
downtime,
refine
protocols,
thereby
optimizing
overall
performance.
The
marks
paradigm
shift,
offering
approach
Leveraging
facilities
fortify
practices.
algorithms
machine
learning
models,
these
empower
forecast
malfunctions
with
unprecedented
accuracy,
allowing
for
timely
interventions
mitigating
potential
risks
benefits
AI-powered
sector
are
multifaceted
industry
is
brimming
promise.
As
continue
evolve,
we
anticipate
further
advancements
analytics,
fault
detection,
decision
support
systems.
embracing
innovation
collaboration,
harness
full
cementing
position
leaders
efficiency.
Язык: Английский
SMART DRILLING TECHNOLOGIES: HARNESSING AI FOR PRECISION AND SAFETY IN OIL AND GAS WELL CONSTRUCTION
Oladiran Kayode Olajiga,
Nwankwo Constance Obiuto,
Riliwan Adekola Adebayo
и другие.
Engineering Science & Technology Journal,
Год журнала:
2024,
Номер
5(4), С. 1214 - 1230
Опубликована: Апрель 10, 2024
This
paper
explores
the
integration
of
AI
in
smart
drilling
technologies,
examining
its
applications,
benefits,
challenges,
and
future
prospects.
By
harnessing
power
AI,
technologies
enable
proactive
decision-making,
automation,
optimization
throughout
lifecycle.
From
well
planning
design
to
real-time
monitoring
control,
AI-driven
systems
improve
operational
performance,
reduce
risks,
maximize
resource
recovery.
Despite
facing
challenges
such
as
data
integration,
technology
adoption,
regulatory
compliance,
potential
benefits
are
substantial.
Enhanced
precision,
improved
safety,
increased
efficiency,
sustainable
practices
among
key
offered
by
these
technologies.
Looking
towards
future,
opportunities
for
further
innovation
advancement
abound,
including
development
advanced
algorithms,
with
IoT
big
analytics,
a
focus
on
environmental
sustainability.
embracing
innovation,
collaboration,
commitment
sustainability,
oil
gas
industry
can
unlock
new
growth
resilience
evolving
landscape
construction.
Smart
hold
promise
reshaping
construction,
paving
way
safer,
more
efficient,
operations
industry.
revolutionizing
industry,
offering
unprecedented
levels
precision
safety
integrating
artificial
intelligence
(AI)
into
processes,
optimize
parameters,
recovery..
sustainability.
Keywords:
drilling,
Artificial
(AI),
Oil
Efficiency,
Safety,
Sustainability.
Язык: Английский
AI-enhanced subsea maintenance for improved safety and efficiency: Exploring strategic approaches
Oludayo Olatoye Sofoluwe,
Obinna Joshua Ochulor,
Ayemere Ukato
и другие.
International Journal of Science and Research Archive,
Год журнала:
2024,
Номер
12(1), С. 114 - 124
Опубликована: Май 5, 2024
As
the
oil
and
gas
industry
increasingly
explores
deeper
more
remote
offshore
sites,
maintenance
of
subsea
infrastructure
becomes
paramount.
The
use
Artificial
Intelligence
(AI)
in
offers
promising
solutions
to
enhance
safety
efficiency
these
challenging
environments.
This
review
strategic
approaches
integrating
AI
into
operations.
facilitates
predictive
by
analyzing
vast
amounts
data
collected
from
sensors
historical
records.
Machine
learning
algorithms
can
detect
patterns
predict
equipment
failures
before
they
occur,
enabling
proactive
scheduling.
capability
reduces
downtime
minimizes
risk
accidents
addressing
potential
issues
escalate.
AI-enabled
autonomous
underwater
vehicles
(AUVs)
remotely
operated
(ROVs)
play
a
crucial
role
inspections
repairs.
These
AI-enhanced
robots
navigate
complex
environments,
perform
inspections,
execute
tasks
with
greater
precision
than
human
divers.
By
reducing
need
for
intervention
hazardous
AI-driven
AUVs
ROVs
significantly
improve
safety.
Furthermore,
optimize
schedules
based
on
factors
such
as
condition,
environmental
conditions,
operational
requirements.
dynamically
adjusting
plans,
operators
maximize
uptime
while
minimizing
costs
risks.
approach
ensures
that
activities
are
conducted
at
most
opportune
times,
likelihood
unplanned
improving
overall
efficiency.
Moreover,
condition-based
strategies,
where
health
is
continuously
monitored
real-time.
Sensors
installed
collect
temperature,
pressure,
vibration,
which
then
analyzed
assess
condition.
detecting
early
signs
degradation
or
malfunction,
enables
timely
interventions,
preventing
costly
breakdowns
ensuring
optimal
performance.
In
addition
maintenance,
analytics
offer
insights
performance
asset
integrity.
various
sources,
including
sensors,
records,
logs,
identify
trends,
anomalies,
optimization
opportunities.
enable
make
data-driven
decisions
system
reliability
Strategic
implementing
require
collaboration
between
technology
providers,
operators,
regulatory
bodies.
Establishing
standards
guidelines
applications
operations
ensure
safety,
reliability,
interoperability.
investing
research
development
robotics
essential
unlock
full
maintenance.
significant
benefits
terms
leveraging
analytics,
robotics,
real-time
monitoring,
activities,
reduce
downtime,
minimize
collaboration,
investment,
commitment
advancing
meet
challenges
Язык: Английский
Monitoring and Improving Aircraft Maintenance Processes Using IT Systems
Applied Sciences,
Год журнала:
2025,
Номер
15(3), С. 1374 - 1374
Опубликована: Янв. 29, 2025
Aircraft
maintenance
is
a
complex,
multifaceted
process
that
greatly
benefits
from
IT
systems
designed
to
improve
supervision,
record
keeping,
and
task
management.
This
study
focuses
on
the
role
of
dedicated
mobile
application,
integrated
into
broader
Maintenance
Support
System,
which
supports
operations
for
M-346
BIELIK
training
aircraft.
highly
intricate
significantly
advanced
enhance
streamline
optimize
explores
pivotal
application
specifically
tailored
support
By
focusing
analysis
Intelligent
Transportation
Systems
(ITSs),
research
highlights
how
contributes
reliability
operational
efficiency,
with
sustainability
considerations
in
mind.
The
ITS-based
approach
assesses
scheduling,
tracking,
resource
optimization,
thereby
enhancing
aircraft
while
reducing
unnecessary
consumption.
alignment
sustainable
practices
not
only
improves
characteristics
exploitation
rates
but
also
positively
impacts
efficiency
effectiveness
aviation
training.
accurately
estimating
time
requirements
specific
tasks
during
periodic
inspections,
aids
identifying
addressing
organizational
bottlenecks,
ultimately
supporting
both
improved
across
activities.
Язык: Английский
Data stream mining techniques for real-time monitoring and control of smart power grids in Kenya: challenges and opportunities
Cornelius Mutuku Mulevu,
George Okeyo,
Joseph Muliaro Wafula
и другие.
Discover Internet of Things,
Год журнала:
2025,
Номер
5(1)
Опубликована: Май 2, 2025
Язык: Английский
Hybrid predictive maintenance model – study and implementation example
Production Engineering Archives,
Год журнала:
2024,
Номер
30(3), С. 285 - 295
Опубликована: Сен. 1, 2024
Abstract
In
this
paper,
the
concept
of
hybrid
predictive
maintenance
for
a
single
industrial
machine
is
presented.
A
review
solutions
in
area
(especially
maintenance)
which
have
been
described
literature
provided.
The
assumptions
model
modules,
machines,
or
systems
are
methods
used
within
developed
methodology
described.
This
includes
use
diagnostic
data,
experience,
and
mathematical
model.
case
study
an
on
system
collecting
diag-nostic
data
has
pilot-implemented,
using,
among
others,
vibration
sensors
drive
pa-rameters
damage
detection
registered
can
be
to
precisely
determine
time
upcoming
failure
after
characteristic
symptoms
resulting
from
component
wear
addition,
analysis
durations
correct
operation
events
was
performed
indicators
describing
these
values
were
determined.
aforementioned
determined
based
empirical
using
gamma
distribution.
objective
research
prepare,
implement
draw
conclusions
real
study.
presented
paper
enables
different
types
(diagnostic,
historical
mathemat-ical
model-based)
scheduling
downtime
actions.
On
basis
re-search
conducted,
it
operating
parameters
characterised
by
varia-bility
that
failure.
allows
precise
planning
activities
minimization
unplanned
downtime.
Язык: Английский
Modeling of Induction Motor Direct Starting with and without Considering Current Displacement in Slot
Applied Sciences,
Год журнала:
2024,
Номер
14(20), С. 9230 - 9230
Опубликована: Окт. 11, 2024
This
article
presents
a
mathematical
model
of
three-phase
induction
motor
(IM)
with
squirrel
cage
rotor
and
investigates
its
starting
modes.
Specifically,
two
scenarios
are
considered:
direct
an
IM
considering
the
current
displacement
effect
in
slots.
Analyzing
modes
without
use
automatic
control
systems
is
crucial
for
ensuring
reliable,
efficient,
safe
operation
equipment
across
various
industrial
commercial
sectors.
Understanding
accounting
processes
occurring
during
mode
allows
minimizing
risks,
enhancing
energy
efficiency,
reducing
operational
costs.
details
modeling
methods
used
analyzing
these
results
obtained
from
modeling.
These
were
compared
data
experimentally,
allowing
assessment
accuracy
reliability
proposed
model.
The
conducted
research
highlights
importance
slots
accurate
analysis
modes,
particularly
capturing
differences
amplitudes
faster
transition
to
steady-state
operation.
Conclusions
drawn
comparison
experimental
provide
valuable
insights
further
development
motors.
Язык: Английский
Investigating the Significance of Virtual Reality in Stimulating Improvement Within Supply Chains
Advances in business information systems and analytics book series,
Год журнала:
2024,
Номер
unknown, С. 321 - 346
Опубликована: Сен. 13, 2024
Virtual
reality
(VR)
technology
is
gaining
traction
for
its
cost-effectiveness
and
benefits,
yet
a
comprehensive
understanding
of
applications
in
supply
chain
operations
essential.
Despite
promise,
VR
adoption
has
been
slower
than
expected
due
to
functional
technological
complexities.
This
research
examines
potential
issues
with
technologies,
explores
operational
roles
across
the
value
chain,
analyzes
factors
contributing
these
challenges.
The
study
uses
data
visualization
from
multiple
studies
investigate
VR's
role
innovation
digitalization,
focusing
on
five
key
aspects:
deployment,
infrastructure,
security,
regulations,
operating
environments.
findings
provide
foundation
future
aimed
at
addressing
challenges
posed
by
paving
way
more
effective
integration
management.
Язык: Английский
Understanding deviations from original equipment manufacturers’ maintenance recommendations: reasons, barriers, and benefits
Ahiamadu Jonathan Okirie,
Mack Barnabas,
Ewomazino Ejomarie
и другие.
Journal of Engineering and Applied Science,
Год журнала:
2024,
Номер
71(1)
Опубликована: Дек. 1, 2024
Abstract
Understanding
why
maintenance
professionals
deviate
from
OEM
recommendations
is
essential.
These
are
crucial
for
ensuring
equipment
reliability,
safety,
and
performance
over
its
operational
lifecycle.
However,
deviations
these
guidelines
common
can
occur
various
reasons.
This
study
seeks
to
enhance
practices
by
analyzing
the
reasons
(RFD)
recommendations,
identifying
barriers
adherence
(BTA),
exploring
potential
benefits
(PB)
of
such
deviations.
To
achieve
this
objective,
a
survey
was
conducted
in
Port
Harcourt,
Southern
Nigeria,
involving
105
personnel
three
maintenance-intensive
sectors:
Oil
Gas,
Energy,
Petrochemicals,
achieved
response
rates
of,
78%,
82%,
92%
respectively.
Through
qualitative
evaluation
data,
research
identified
cost
considerations
constraints
as
primary
non-adherence
guidelines.
Respondents
highlighted
savings
enhanced
availability,
citing
limited
budgets
demands
significant
compliance.
Comparative
analysis
across
deviant
factors
(RFD,
BTA,
PB)
underscores
dominance
cost-related
driving
deviations,
alongside
technological
influences,
that
both
facilitate
impede
adherence.
Environmental
organizational
factors,
though
influential,
exhibit
comparatively
lesser
impact.
findings
highlight
significance
aligning
with
recommendations.
alignment
not
only
enhances
reliability
reduces
risks
but
also
has
improve
practices,
foster
innovation
industry,
ultimately
optimize
industrial
settings.
Язык: Английский