Transcript chapter-20

20–1
Chapter Twenty
McGraw-Hill/Irwin
Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved.
20–2
• LO20–2: Analyze how different
inventory control systems work
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• LO20–1: Explain how inventory is used
and understand what it costs
• LO20–3: Analyze inventory using the
Pareto principle
20–3
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• Inventory can be visualized as stacks of money
sitting on forklifts, on shelves, and in trucks and
planes while in transit.
• For many businesses, inventory is the largest
asset on the balance sheet at any given time.
• Inventory can be difficult to convert back into
cash.
• It is a good idea to try to get your inventory
down as far as possible.
– The average cost of inventory in the United States
is 30 to 35 percent of its value.
20–4
20–5
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• Used when we are making a one-time purchase of an
item
Fixed-order quantity model
• Used when we want to maintain an item “in-stock,” and
when we restock, a certain number of units must be
ordered
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Single-period model
Fixed–time period model
• Item is ordered at certain intervals of time
20–6
– Includes raw materials, finished products,
component parts, supplies, and work-in-process
– Manufacturing inventory: refers to items that
contribute to or become part of a firm’s product
• Inventory system: the set of policies and
controls that monitor levels of inventory
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• Inventory: the stock of any item or resource
used in an organization
– Determines what levels should be maintained,
when stock should be replenished, and how large
orders should be
20–7
To meet variation in
product demand
To provide a
safeguard for
variation in raw
material delivery
time
To allow flexibility
in production
scheduling
To take advantage
of economic
purchase order size
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To maintain
independence of
operations
20–8
• Costs for storage, handling,
insurance, and so on
Setup (or production
change) costs
• Costs for arranging specific
equipment setups, and so on
Costs
Ordering costs
Shortage costs
• Costs of placing an order
• Costs of running out
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Holding (or carrying) costs
20–9
• For example, a workstation may produce
many parts that are unrelated but meet
some external demand requirement
Dependent demand – the need
for any one item is a direct result
of the need for some other item
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Independent demand – the
demands for various items are
unrelated to each other
• Usually a higher-level item of which it is
part
20–10
20–11
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• One-time purchasing decision
(e.g., vendor selling T-shirts at a
football game)
• Seeks to balance the costs of
inventory overstock and under
stock
Multi-period inventory models
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Single-period inventory
model
• Fixed-order quantity models
• Event triggered (e.g., running out of
stock)
• Fixed-time period models
• Time triggered (e.g., monthly sales call
by sales representative)
20–12
Too few papers and some
customers will not be able
to purchase a paper, and
profits associated with
these potential sales are
lost.
Too many papers and the
price paid for papers that
were not sold during the
day will be wasted,
lowering profit.
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Consider the problem of
deciding how many newspapers
to put in a hotel lobby
20–13
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• Consider how much risk we are willing to take of running out
of inventory.
• Assume a mean of 90 papers and a standard deviation of 10
papers.
• Assume we want an 80 percent chance of not running out.
• Assume that the probability distribution associated of sales is
normal, stocking 90 papers yields a 50 percent chance of
stocking out.
20–14
– Using Excel, “=NORMSINV(0.8)” =
0.84162
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• From Appendix E, we see that we
need approximately 0.85 standard
deviation of extra papers to be 80
percent sure of not stocking out.
20–15
Co = cost per unit of demand over stocking level
Cu = cost per unit of demand under stocking level
P = probability that a given unit will be sold
• We should increase the size of the
inventory so long as the probability of
selling the last unit added is equal to or
𝐶𝑢
greater than the ratio
𝐶𝑜+𝐶𝑢
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Where:
𝑃 ≤
𝐶𝑢
𝐶𝑜+𝐶𝑢
20–16
=
800
200+80
= 0.2857
• Mean demand is 5
– Standard deviation of demand is 3
– Room rate is $80 (this is the cost if overbookings
are less than cancelations - Cu)
– Penalty for overbooking is $200 (this is the cost if
overbookings are more than cancelations - Co)
For the Excel template visit
www.mhhe.com/sie-chase14e
Excel:
Overbooking
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𝑃 ≤
𝐶𝑢
𝐶𝑜+𝐶𝑢
20–17
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• From Appendix E, we see that our
desired level falls about 0.55 standard
deviations below the mean (z = -0.55)
– Using Excel, “=NORMSINV(0.2857)”
= 0.56599
20–18
If we overbook by 1 and
we have three no-shows,
we have lost sales of $80.
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If we overbook by 1 and
we have zero no-shows,
we incur the penalty of
$200 – one person must
be compensated for
having no room.
Total cost of a policy of
overbooking by 9 rooms
is the weighted average
of the events (number of
no-shows) and the
outcome of those events.
20–19
Ordering of clothing and other fashion items
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Overbooking of airline flights
One-time order for events – e.g., t-shirts for a
concert
20–20
- Also called the economic
order quantity, EOQ, and Q-
model
- Event triggered
Fixed–time period models
- Also called the periodic system,
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Fixed-order quantity models
periodic review system, fixed-
order interval system, and P-mode
- Time triggered
20–21
– Inventory remaining must
be continually monitored
– Has a smaller average
inventory
– Favors more expensive
items
– Is more appropriate for
important items
– Requires more time to
maintain – but is usually
more automated
– Is more expensive to
implement
• Fixed-Time Period
– Counting takes place
only at the end of the
review period
– Has a larger average
inventory
– Favors less expensive
items
– Is sufficient for lessimportant items
– Requires less time to
maintain
– Is less expensive to
implement
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• Fixed-Order Quantity
20–22
20–23
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20–24
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Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved.
• Demand for the product is constant and uniform
throughout the period.
• Lead time (time from ordering to receipt) is
constant.
• Price per unit of product is constant.
• Inventory holding cost is based on average
inventory.
• Ordering or setup costs are constant.
• All demands for the product will be satisfied.
20–25
Inventory is consumed at a
constant rate, with a new
order placed when the
reorder point (R) is reached
once again.
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Always order Q units when
inventory reaches reorder
point (R).
Inventory arrives after
lead time (L). Inventory is
raised to maximum level
(Q).
20–26
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The optimal order
quantity (Qopt) occurs
where total costs are at
their minimum
20–27
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• Annual demand (D) =
1,000 units
– Average daily demand
𝑑 = 1000
= 2.74
365
units
– Ordering cost (S) = $5
per order
– Holding cost (H) = $1.25
per unit per year
– Lead time (L) = 5 days
– Cost per unit (C) =
$12.50
For the Excel template visit
www.mhhe.com/sie-chase14e
Excel: Economic
Order Quantity
20–28
• Safety stock can be determined based on many different criteria.
A common approach is to simply keep a certain number
of weeks of supply.
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Safety stock – refers to the amount of inventory carried
in addition to expected demand.
A better approach is to use probability.
•Assume demand is normally distributed.
•Assume we know mean and standard deviation.
•To determine probability, we plot a normal distribution for expected demand and
note where the amount we have lies on the curve.
20–29
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Demand is variable, but
follows a known
distribution/
After the reorder is placed, demand
during the lead time may be higher
than expected, consuming some (or
all) of the safety stock/
20–30
(𝑑) = 60
For 95%
probability,
z = 1.64.
• Annual demand (D) =
60(365) = 21,900
• Standard deviation of
demand during lead time
(σD) = 7
• Ordering cost (S) = $10 per
order
• Holding cost (H) = $0.50 per
unit per year
• Lead time (L) = 6 days
For the Excel template visit
www.mhhe.com/sie-chase14e
Policy – place a new
order for 936 units
whenever stock falls
to 388 units on hand.
This results in a 95%
probability of not
stocking out during
the lead time.
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• Average daily demand
Excel: Reorder
Point
20–31
q = quantity to be ordered
T = number of days between reviews
L = lead time in days
𝑑 = forecast average daily demand
Z = number of standard deviations required for
specific service level
• σT+L= standard deviation of demand during the review
and lead time
• I = current inventory level (including items on order)
Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved.
•
•
•
•
•
𝑞 = 𝑑 𝑇 + 𝐿 + 𝑧𝜎𝑇+𝐿
20–32
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Time periods
are equal, but
ending
inventory
varies.
Reorder quantity varies,
depending upon ending
inventory level. Beginning
inventory is always the
same.
20–33
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• Daily demand (𝑑) of 10
units
• Daily standard deviation
(𝜎𝐷 ) of 3 units
• Review period (T) of 30
days
• Lead time (L) of 14 days
• 98 percent of demand
should be met from items
in stock
• 150 units in inventory (I)
For the Excel template visit
www.mhhe.com/sie-chase14e
Excel: Fixed
Time Period
Model
20–34
• Inventory turns –
number of times
inventory is cycled
through over time –
a measure of how
efficiently inventory
is used
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• Average inventory –
expected amount of
inventory over time
20–35
• To find the lowest-cost, calculate the order
quantity for each price and see if the quantity
is feasible.
– Sort prices from lowest to highest and calculate the
order quantity for each price until a feasible order
quantity is found.
– If the first feasible order quantity is the lowest price,
this is best; otherwise, calculate the total cost for the
first feasible quantity and calculate total cost at each
price lower than the first feasible order quantity.
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• Price varies with the order size.
20–36
20–37
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– 1–499 → $5.00
– 500–999 → $4.50
– 1000 or more → $3.90
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• Annual demand (D ) =
10,000
• Ordering cost (S ) =
$20 per order
• Interest/carrying cost
(i ) = 20%
• Cost per unit (C )
20–38
20–39
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20–40
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Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved.
Inventory accuracy –
refers to how well the
inventory records agree
with physical count
Cycle counting – a
physical inventory-taking
technique in which
inventory is counted on a
frequent basis rather
than once or twice a year
20–41