It
is
known
from
Phase
I
data
that
a
process
has
the
average
defects
rate
of
60
defects
per
1000
boards.
(a)
One
engineer
suggests
a
sampling
strategy
to
make
quality
checking
every
hour
by
selecting
100
boards,
how
to
construct
a
3-sigma
monitoring
chart
(CL,
UCL,
and
LCL)?
(1
point)
(b)
How
many
boards
should
be
checked
at
each
sampling
hour
to
obtain
a
positive
lower
control
limit?
(0.5
points)
(c)
One
month
later,
this
engineer
decided
to
change
the
sampling
strategy
by
checking
400
boards
at
each
sampling
hour
by
considering
the
increased
production
throughput.
Under
this
new
sampling
strategy,
how
do
you suggest
for
continuously
monitoring
such
a
process
(selecting
a
¢
chart
or
u
chart)
and
why?
Please
define
the
random
variable
that
follows
the
Poisson
distribution
and
provide
the
distribution
parameter
correspondingly.
(0.5
points)
(The
process’s
Phase
I
condition
has
not
changed)
(d)
For
(c),
if
a
u
chart
is
suggested
with
a
convenient
unit
=100
boards,
what
is
the
sample
size
n
in
the
u
chart?
What
are
the
corresponding
control
limits
of
this
u
chart
(CL,
UCL,
and
LCL,
L=3)?
What
are
c0
and
u0
when
the
process
is
in-control?
(1
points)
(e)
If
at
time
t,
it
is
found
that
a
sample
of
400
boards
has
28
defects,
what
are
the
monitoring
statistics
to
be
plotted
in
the
¢
and
u
charts
after
the
change
in
(c)? (0.5
points)
