Systems,
Journal Year:
2024,
Volume and Issue:
12(11), P. 479 - 479
Published: Nov. 11, 2024
Human
errors
(HEs)
are
prevalent
issues
in
manual
assembly,
leading
to
product
defects
and
increased
costs.
Understanding
knowing
the
factors
influencing
human
assembly
processes
is
essential
for
improving
quality
efficiency.
This
study
aims
determine
rank
HEs
based
on
expert
judgments.
To
achieve
this
objective,
an
integrated
model
was
developed
using
two
multi-criteria
decision-making
(MCDM)
techniques—specifically,
fuzzy
Delphi
Method
(FDM)
Analytic
Hierarchy
Process
(FAHP).
Firstly,
rounds
of
FDM
were
conducted
identify
categorize
primary
contributing
assembly.
Expert
consensus
with
at
least
75%
agreement
determined
that
27
influence
scores
0.7
or
higher
significantly
impact
these
processes.
After
that,
priorities
a
third
round
FAHP
method.
Data
analysis
performed
SPSS
22.0
evaluate
reliability
normality
survey
responses.
has
divided
affecting
into
levels:
level
1,
called
main
factors,
2,
sub-factors.
Based
final
measured
weights
proposed
estimation
results
revealed
most
influential
individual
factor,
followed
by
tool
factor
task
factor.
For
showed
lack
experience,
poor
instructions
procedures,
misunderstanding
as
critical
errors.
Sensitivity
how
changes
inputs
parameters
affect
decisions
ensure
reliable
practical
results.
The
findings
provide
valuable
insights
help
organizations
develop
effective
strategies
reducing
worker
Identifying
key
root
errors,
research
offers
solid
foundation
enhancing
overall
products.
Ocean Engineering,
Journal Year:
2024,
Volume and Issue:
312, P. 119078 - 119078
Published: Aug. 29, 2024
The
distinctive
features
of
maritime
infrastructures
present
significant
challenges
in
terms
security.Disruptions
to
the
normal
functioning
any
part
transportation
can
have
wide-ranging
consequences
at
both
national
and
international
levels,
making
it
an
attractive
target
for
malicious
attacks.Within
this
context,
integration
digitalization
technological
advancements
seaports,
vessels
other
elements
exposes
them
cyber
threats.In
response
critical
challenge,
paper
aims
formulate
a
novel
cybersecurity
risk
analysis
method
ensuring
security.This
approach
is
based
on
data-driven
Bayesian
network,
utilizing
recorded
incidents
spanning
past
two
decades.The
findings
contribute
identification
highly
contributing
factors,
meticulous
examination
their
nature,
revelation
interdependencies,
estimation
probabilities
occurrence.Rigorous
validation
developed
model
ensures
its
robustness
diagnostic
prognostic
purposes.The
implications
drawn
from
study
offer
valuable
insights
stakeholders
governmental
bodies,
enhancing
understanding
how
address
threats
affecting
industry.This
knowledge
aids
implementation
necessary
preventive
measures.
Journal of Marine Engineering & Technology,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 20
Published: Oct. 15, 2024
Maritime
Autonomous
Surface
Ships
(MASS)
have
gained
much
attention
as
a
safer
and
more
efficient
mode
of
transportation
potential
solution
to
reduce
the
workload
seafarers.
Despite
highly
sophisticated
autonomous
systems
that
enable
MASS
make
independent
decisions,
presence
humans
on
board
or
in
loop
safety
management
highlights
need
for
effective
human-machine
interaction.
However,
potentially
systematic
review
critical
aspects
human-MASS
interaction
has
not
yet
been
conducted.
In
this
paper,
we
aim
fill
gap
by
reviewing
literature
related
from
four
crucial
perspectives:
state
art
interaction,
situational
awareness
MASS,
collision
avoidance
methods
within
mixed
waterborne
transport
system
(MWTS),
human
trust
MASS.
Our
reveals
efficiency
mainly
focuses
key
aspects:
(i)
factors,
(ii)
available
technologies
supporting
autonomy
(iii)
analysis
design
(iv)
requirements
regarding
regulations.
Moreover,
provide
detailed
discussion
three
fundamental
factors
influence
including
awareness,
decision-making
system,
Finally,
based
our
analysis,
propose
an
integrated
framework
which
these
are
taken
into
account.
We
anticipate
their
will
receive
improve
