Review for BMGT 385 Final

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Unformatted text preview: Review
for
BMGT
385
Final
–
Fall
2009
 
 
 
 Professor
Elmaghraby
 The
final
is
comprehensive;
however,
there
will
be
a
strong
emphasis
on
the
 material
that
we
covered
after
the
material.
You
can
expect
that
no
less
than
75%
of
 the
material
will
come
from
the
second
half
of
the
semester.
 
 The
format
will
be
similar
to
the
midterm
–
the
exam
will
consist
of
multiple
choice
 plus
T/F
questions.
 I
have
outlined
here
the
various
concepts
that
we
have
covered
since
the
midterm.
 You
can
find
at
the
end
of
this
document
a
list
of
equations
that
will
be
attached
to
 your
exam.
 You
will
also
be
given
the
standard
normal
tables,
as
well
as
the
standard
normal
 Loss
function
tables.
 
 Topic:
Variability
and
Queues
 Concepts
covered:
 1)
Understanding
how
queues
form
even
when
there
is
enough
capacity
(utilization
 <
100%)
 2)
Defining
elements
of
a
queue:

 Customers,

their
inter‐arrival
times
(
defined
as
time
between
two
successive
 arrivals)
and
the
variability
of
their
inter‐arrival
times
(measured
through
the
 coefficient
of
variation).

 Server(s),

processing
times,
and
the
variability
of
the
processing
time
 (measured
through
the
coefficient
of
variation)
 Lines/Queues
 3)
Process
Measurements
of
interest
 
 Utilization
 Inventory
of
customers
in
Queue
(i.e.,
length
of
queue)
 Inventory
of
customers
in
system
 
 
 Number
of
Servers
 Waiting
time
in
Queue


 Flow
Time
in
the
System
 
 
 •Managing
and
designing
queues
 Pooling
of
queues
 Superserver
 Topic:
Inventory
Management
 Concepts
Covered:
 
 1)
Why
firms
hold
inventory
and
why
it
is
costly
to
hold
inventory
 2)
Study
different
inventory
systems:

the
set
of
policies
and
controls
that
monitor
 levels
of
inventory
and
determines
what
levels
should
be
maintained,
when
stock
 should
be
replenished,
and
how
large
orders
should
be
 
 3)
Single‐Period
Inventory
Model:
Newsvendor
Model
 –One
time
purchasing
decision
(Example:
vendor
selling
t‐shirts
at
a
football
 game)
 –Seeks
to
balance
the
costs
of
inventory
overstock
(overage
cost)
and
under
 stock
(underage
cost)
 
‐
Key
thing
driving
the
newsvendor
problem
is
the
uncertainty
regarding
 demand
(order/inventory
decision
must
be
made
before
demand
is
realized)
 
‐
Companies
often
use
forecasting
performance
on
similar
items
to
help
 develop
a
distribution
to
characterize
the
uncertainty
in
demand

 
‐
Many
ways
to
select
order
quantity:
The
Critical
Ratio
defines
order
 quantity
that
minimized
expected
costs
 
 
‐
Alternatively,
management
may
be
interested
in
alternative
performance
 characteristics,
such
as:
 
 
 i)
Expected
Fill
Rate:
The
fraction
of
demand
that
is
satisfied
 immediately
 ii)
In‐stock
probability:
Probability
all
demand
is
satisfied

 iii)
Stockout
probability:
Probability
some
demand
is
lost
 
 For
any
of
these
objectives/perfomance
characteristics,
once
we’ve
identified
 the
order
quantity
to
achieve
this
goal,
we
can
also
calculate
the
following
 performance
metrics:
 a)
Expected
lost
sales:
The
average
number
of
units
demand
exceeds
 the
order
quantity
 b)
Expected
sales
:
The
average
number
of
units
sold.
 c)
Expected
left
over
inventory:
The
average
number
of
units
left
over
 at
the
end
of
the
season.
 d)
Expected
profit
 
 4)
Multi‐Period
Inventory
Models
 
 ‐ Inventory
Managers
face
two
fundamental
decisions
when
ordering
in
a
 repeat
environment:
When
to
order
items
from
a
supplier
or
when
to
 initiate
production
runs
and
How
much
to
order
or
produce
each
time
a
 supplier
or
production
order
is
placed.
 
 If
the
manager
is
free
to
select
both
of
these
policies
then
the
key
trade‐ off
is
fixed
(ordering)
costs
versus
variable
(holding)
costs
 ‐ 
 ‐ 
 ‐ When
demand
is
deterministic
–
the
EOQ
quantity
emerges
as
the
optimal
 decision
for
how
much.
 When
demand
is
deterministic
–
orders
should
be
placed
when
inventory
 level
reaches
R
(reorder
point)
–
R
is
such
that
new
order
is
received
as
 soon
as
inventory
level
hits
zero.
 
 ‐ When
demand
is
random,
then
management
should
keep
some
safety
 stock
in
order
to
hedge
against
the
uncertainty
in
demand:
Management
 needs
to
hedge
against
uncertainty
in
demand
during
leadtime
L.
 
 ‐ When
demand
is
random
and
management
can
order
whenever
it
needs
 to
do
so,
reorder
point
is
set
so
as
to
achieve
a
desired
service
level/in‐ stock
probability.
 
 ‐ When
demand
is
random
and
management
must
order
at
fixed
time
 periods,
then
the
order
quantity
is
adjusted
to
achieve
the
desired
service
 level
of
the
length
of
the
leadtime
plus
order
cycle
minus
whatever
 inventory
is
in
stock.
 
 Topic:
Quality
 Concepts
Covered:
 
 1)
Variability
is
detrimental
to
quality
because
it
may
result
in
wasted
resources
and
 reduced
capacity
 
 2)
There
are
two
causes
of
Variability:
Common
(chance
or
natural)
causes
and
then
 Assignable
causes.
 
 3)
We
use
statistical
sampling
and
control
charts
to
help
us
tease
out
assignable‐
 cause
variation
from
common
cause
variation.
 
 If
you
are
measuring
a
variable
data
–
then
X‐bar
and
R
charts
are
the
 appropriate
tools.
If
you
are
measuring
attribute
data
–
then
a
p‐chart
is
 appropriate.
If
variability
is
purely
random,
then
99.7%
of
the
sample
means
 (ranges)
should
fall
within
these
intervals.


 
 4)
Understanding
“Process
capability”

‐
the
ability
of
a
process
to
meet
the
firm’s
 expectations/quality
standards.

 A
process
may
be
in‐control
and
yet
unable
to
meet
a
firm’s
requests
quality
 standards
(i.e.,
there
is
too
much
common
cause
variation
in
the
process)
 
 
 •Quality
and
Throughput
Losses
 
 Topic:
Lean
Manufacturing
 
 Concepts
Covered:

 
 1)
BIT
JIT/Lean
Manufacturing
Philosophy:

 Setup
cost
should
be
reduced,
not
just
balanced
against
inventory
cost


 Safety
stock
is
undesirable.

‐
produce
only
when
it
is
needed
 High
productivity
and
quality
are
essential.
 2)
All
forms
of
waste
must
be
eliminated
from
the
process

 
 
 
 ...
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