Revista Produção Online,
Год журнала:
2024,
Номер
24(2), С. 5151 - 5151
Опубликована: Июнь 17, 2024
The
aim
of
this
paper
is
to
develop
a
manufacturing
maturity
model
for
implementing
Industry
4.0
technologies.
study
was
based
on
the
methodology
De
Bruin
et
al.
(2005).
contributes
by
providing
insights
into
how
can
help
companies
see
their
strengths
and
weaknesses
in
order
improve
level
these
organizations.
specifically
developed
specified
objectives,
factors
barriers,
addressing
complexity
with
focus
manufacturing.
To
end,
questionnaire
administered
25
employees
Espírito
Santo,
Brazil,
validating
found
identifying
organizations
studied.
consists
five
levels,
three
dimensions
27
elements.
applied
resulted
59.7%,
obtaining
an
intermediate
classification,
meaning
partial
use
technologies
A
comparison
made
between
Mining,
Electrical,
IT,
Steel
Metallurgy
sectors.
results
showed
that
Mining
sectors
have
highest
values
IT
lowest
values.
limitation
subjectivity
inherent
questionnaires.
As
future
suggestion,
it
possible
identify
relationships
elements
presented
model.
International Journal of Artificial Intelligence & Applications,
Год журнала:
2024,
Номер
15(1), С. 57 - 69
Опубликована: Янв. 29, 2024
This
study
reviews
studies
on
Artificial
Intelligence
(AI)
maturity
models
(MM)
in
automotive
manufacturing.
To
stay
competitive,
SMEs
the
industry
need
to
embrace
digitalization.
employ
a
large
segment
of
USA's
workforce.
The
benefits
operational
efficiency,
quality
improvement,
cost
reduction,
and
innovative
culture
have
made
more
aggressive
about
Digitalizing
operations
with
are
rise.
In
this
paper,
AI
applications
examined
through
lens
an
model.
Journal of Industrial Engineering and Management,
Год журнала:
2024,
Номер
17(1), С. 196 - 196
Опубликована: Фев. 29, 2024
Purpose:
This
research
investigates
Portuguese
manufacturing
companies'
Industry
4.0
(I4.0)
maturity
perception
level
and
proposes
an
index
to
measure
that
aim.Design/methodology/approach:
study
uses
a
survey
method
gather
the
perceptions
of
their
I4.0
applies
subsequent
exploratory
factor
analysis
propose
global
measurement
index.Findings:
The
results
show
most
critical
factors
in
evaluating
Perception
Maturity
(IPM)
are
strategy,
leadership,
customer
experiences.
result
for
Global
Index
was
53.50%.
Hence,
Portugal
is
medium.Research
limitations/implications:
encompasses
only
organizations
(50
valid
responses).
Moreover,
subject
limitations
methodology,
such
as
possible
respondent
bias.Practical
implications:
strategy
mainly
targets
small
medium-sized
enterprises
through
bottom-up
approach.
companies
need
proper
methodologies
tools
adoption,
identifying
present
situation
concerning
where
focus
on
improving
process
achieving
intended
benefits.Social
identifies
main
perceived
benefits
obstacles
adopting
I4.0,
suggesting
avenues
its
successful
implementation
by
companies.Originality/value:
provides
valuable
tool
identify
be
improved
create
significant
growth
index.
Therefore,
it
can
support
establishing
roadmap
adoption
performance
competitive
position
accordingly.
Sustainability,
Год журнала:
2024,
Номер
16(12), С. 5005 - 5005
Опубликована: Июнь 12, 2024
The
development
of
batteries
used
in
electric
vehicles
towards
sustainable
poses
challenges
to
designers
and
manufacturers.
Although
there
has
been
research
on
the
analysis
environmental
impact
during
their
life
cycle
(LCA),
is
still
a
lack
comparative
analyses
focusing
first
phase,
i.e.,
extraction
processing
materials.
Therefore,
purpose
this
was
perform
detailed
popular
vehicle
batteries.
method
based
burdens
regarding
ecological
footprint
materials
for
vehicles.
Popular
were
analyzed:
lithium-ion
(Li-Ion),
lithium
iron
phosphate
(LiFePO4),
three-component
nickel
cobalt
manganese
(NCM).
criteria
carbon
dioxide
emissions,
land
use
(including
modernization
development)
nuclear
energy
emissions.
This
data
from
GREET
model
Ecoinvent
database
OpenLCA
programme.
results
showed
that
considering
loads
footprint,
most
advantageous
point
view
turned
out
be
battery.
At
same
time,
key
occurring
phase
LCA
these
identified,
e.g.,
production
electricity
using
hard
coal,
quicklime,
enrichment
rocks
(wet),
phosphoric
acid,
uranium
mine
operation
process.
To
reduce
burdens,
improvement
actions
are
proposed,
resulting
synthesized
review
literature.
may
useful
design
stages
new
constitute
basis
undertaking
pro-environmental
toward
already
present
market.
In
the
present
era,
manufacturing
sector
is
experiencing
two
distinct
revolutions.
Industry
4.0
emphasizes
machine
autonomy,
digitization,
and
problem-solving
without
human
intervention.
On
other
hand,
industry
5.0
represents
a
paradigm
shift
that
goes
beyond
productivity
efficiency,
focusing
on
reintegrating
humans
into
production
process
recognizing
their
value.
To
remain
competitive,
companies
must
keep
up
with
these
trends
advancements.
Initially,
they
faced
challenges
in
adapting
to
automation
level
of
4.0,
but
now
embrace
new
era
enhance
performance.
Consequently,
it
crucial
assess
maturity
order
establish
roadmap
for
implementing
5.0.
This
paper
conducts
an
exploratory
literature
review
106
research
papers,
selected
from
pool
181
publications
obtained
Scopus
Web
Science
databases
analyzed
NVIVO.
The
study
occurs
qualitative
by
analyzing
word
usage
through
cloud,
delve
connections
between
those
words
particular
subjects
examine
existing
models.
guided
us
towards
focal
point
where
intersection
models
promises
rich
opportunities
investigation
contribution.
Revista Produção Online,
Год журнала:
2024,
Номер
24(2), С. 5151 - 5151
Опубликована: Июнь 17, 2024
The
aim
of
this
paper
is
to
develop
a
manufacturing
maturity
model
for
implementing
Industry
4.0
technologies.
study
was
based
on
the
methodology
De
Bruin
et
al.
(2005).
contributes
by
providing
insights
into
how
can
help
companies
see
their
strengths
and
weaknesses
in
order
improve
level
these
organizations.
specifically
developed
specified
objectives,
factors
barriers,
addressing
complexity
with
focus
manufacturing.
To
end,
questionnaire
administered
25
employees
Espírito
Santo,
Brazil,
validating
found
identifying
organizations
studied.
consists
five
levels,
three
dimensions
27
elements.
applied
resulted
59.7%,
obtaining
an
intermediate
classification,
meaning
partial
use
technologies
A
comparison
made
between
Mining,
Electrical,
IT,
Steel
Metallurgy
sectors.
results
showed
that
Mining
sectors
have
highest
values
IT
lowest
values.
limitation
subjectivity
inherent
questionnaires.
As
future
suggestion,
it
possible
identify
relationships
elements
presented
model.
