chapter 10: inventory
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Chapter 10: Inventory. Types of Inventory and Demand Availability Cost vs. Service Tradeoff Pull vs. Push Reorder Point System Periodic Review System Joint Ordering Number of Stocking Points Investment Limit Just-In-Time. Chapter 10: Inventory. Skip the following: - PowerPoint PPT PresentationTRANSCRIPT
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Chapter 10: Inventory
• Types of Inventory and Demand
• Availability
• Cost vs. Service Tradeoff
• Pull vs. Push
• Reorder Point System
• Periodic Review System
• Joint Ordering
• Number of Stocking Points
• Investment Limit
• Just-In-Time
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Chapter 10: Inventory
• Skip the following:– Single-Order Quantity: pp. 322-323– Lumpy Demand: pp. 344-345, – Box 10.23 Application: pp. 347-348, – Poisson Distribution: pp. 356-357)
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Inventory
• Inventory includes:– Raw materials, Supplies, Components, Work-in-progress,
Finished goods.
• Located in:– Warehouses, Production facility, Vehicles, Store shelves.
• Cost is usually 20-40% of the item value per year!
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Why Keep Inventories?
• Positive effects:– Economies of scale in production & transportation.
– Coordinate supply and demand.
– Customer service.
– Part of production.
• Negative Effects:– Money tied up could be better spent elsewhere.
– Inventories often hide quality problems.
– Encourages local, not system-wide view.
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Types of Inventories
• Regular (cycle) stock: to meet expected demand between orders.
• Safety stock: to protect against unexpected demand.– Due to larger than expected demand or longer than expected lead
time.– Lead time=time between placing and receiving order.
• Pipeline inventory: inventory in transit.
• Speculation inventory: precious metals, oil, etc.
• Obsolete/Shrinkage stock: out-of-date, lost, stolen, etc.
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Types of Demand
• Perpetual (continual): – Mean and standard deviation (or variance) of demand are known (or can be
calculated).– Use repetitive ordering.
• Seasonal or Spike: – Order once (or a few time) per season.
• Lumpy: hard to predict.– Often standard deviation > mean.
• Terminating: – Demand will end at known time.
• Derived (dependent): – Depends on demand for another item.
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Performance Measures
• Turnover ratio:
• Availability:– Service Level = SL– Fill Rate = FR– Weighted Average Fill Rate = WAFR
Annual demand
Average inventoryTurnover ratio =
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Measuring Availability: SL
• Want product available in the right amount, in the right place, at the right time.
• For 1 item: SLi = Service Level for item iSLi = Probability that item i is in stock.
= 1 - Probability that item i is out-of-stock.
Expected number of units out of stock/year for item iAnnual demand for item i
SLi = 1 -
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Measuring Availability: FR and WAFR
• For 1 order of several items: FRj = Fill Rate for order jFRj = Product of service levels for items ordered.
• For all orders: WAFR (Weighted Average Fill Rate)– Sum over all orders of (FRj) x (frequency of order j).
FRj = SL1 x SL2 x SL3 x ...
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WAFR Example
• Example: 3 items – I1 (SL=0.98); I2 (SL = 0.90); I3 (SL = 0.95)
Order Frequency FR Freq.xFRI1 0.4 0.98 0.392I1,I2,I2 0.1 0.98x0.90x0.90=0.7938 0.07938I1,I3 0.2 0.98x0.95=0.931 0.1862I1,I2,I3 0.3 0.98x0.90x0.95=0.8379 0.25137
WAFR = 0.90895
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Fundamental Tradeoff
• Level of Service vs. Cost
Level of Service
$
Cost
Revenue
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Fundamental Tradeoff
• Level of Service (availability) vs. Cost
• Higher service levels -> More inventory.-> Higher cost.
• Higher service levels -> Better availability.-> Fewer stockouts.-> Higher revenue.
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Inventory Costs
• Procurement (order) cost: – To prepare, process, transmit, handle order.
• Carrying or Holding cost: – Proportional to amount (average value) of inventory.– Capital costs - for $ tied up (80%). – Space costs - for space used.– Service and risk costs - insurance, taxes, theft, spoilage, obsolecence, etc.
• Out-of-stock costs (if order can not be filled from stock).– Lost sales cost - current and future orders.– Backorder cost - for extra processing, handling, transportation, etc.
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Fundamental Cost Tradeoff
Inventory carrying cost vs. Order & Stockout cost
• Larger inventory -> Higher carrying costs.
• Larger inventory -> Fewer larger orders.-> Lower order costs.
• Larger inventory -> Better availability. -> Few stockouts.
-> Lower stockout costs.
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Retail Stockouts
On average 8-12% of items are not available!
• Causes:– Inadequate store orders.
– Not knowing store is out-of-stock.
– Poor promotion forecasting.
– Not enough shelf space.
– Backroom inventory not restocked.
– Replenishment warehouse did not have enough • True for only 3% of stockouts.
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Pull vs. Push Systems
• Pull:– Treat each stocking point independent of others. – Each orders independently and “pulls” items in.– Common in retail.
• Push: – Set inventory levels collectively.– Allows purchasing, production and transportation economies
of scale.– May be required if large amounts are acquired at one time.
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Push Inventory Control
• Acquire a large amount.
• Allocate amount among stocking points (warehouses) based on:– Forecasted demand and standard deviation.– Current stock on hand.– Service levels.
• Locations with larger demand or higher service levels are allocated more.
• Locations with more inventory on hand are allocated less.
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Push Inventory Control
TRi = Total requirements for warehouse i
NRi = Net requirements at i
Total excess = Amount available - NR for all warehouses
Demand % = (Forecast demand at i)/(Total forecast demand)
Allocation for i = NRi + (Total excess) x (Demand %)
= Forecast demand at i + Safety stock at i
= Forecast demand at i + z x Forecast error at i
= TRi - Current inventory at i z is from Appendix A
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Push Inventory Control Example
Allocate 60,000 cases of product among two warehouses based on the following data.
Current Forecast ForecastWarehouse Inventory Demand Error SL 1 10,000 20,000 5,000 0.90 2 5,000 15,000 3,000 0.98
35,000
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Push Inventory Control Example
Current Forecast Forecast DemandWarehouse Inventory Demand Error SL % 1 10,000 20,000 5,000 0.90 0.5714
2 5,000 15,000 3,000 0.98 0.4286 35,000
TR1 = 20,000 + 1.28 x 5,000 = 26,400TR2 = 15,000 + 2.05 x 3,000 = 21,150
NR1 = 26,400 - 10,000 = 16,400NR2 = 21,150 - 5,000 = 16,150
Total Excess = 60,000 - 16,400 - 16,150 = 27,450
Allocation for 1 = 16,400 + 27,450 x (0.5714) = 32,086 casesAllocation for 2 = 16,150 + 27,450 x (0.4286) = 27,914 cases
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Pull Inventory Control - Repetitive Ordering
• For perpetual (continual) demand.
• Treat each stocking point independently.
• Consider 1 product at 1 location.
Determine:
How much to order:
When to (re)order:
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Pull Inventory Control - Repetitive Ordering
• For perpetual (continual) demand.
• Treat each stocking point independently.
• Consider 1 product art 1 location.
Reorder Periodic
Determine: Point System Review System
How much to order: Q M-qi
When to (re)order: ROP T
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Reorder Point System
Order amount Q when inventory falls to level ROP.• Constant order amount (Q).• Variable order interval.
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Reorder Point System
Receive 1st order
Place 1st order
Receive 2nd order
Place 2nd order Receive
3rd order
Place 3rd order
LT1 LT2 LT3
Each increase in inventory is size Q.
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Reorder Point System
Receive 1st order
Place 1st order
Receive 2nd order
Place 2nd order Receive
3rd order
Place 3rd order
LT1 LT2 LT3
Time between 1st & 2nd order
Time between 2nd & 3rd order
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Periodic Review System
Order amount M-qi every T time units.
• Constant order interval (T=20 below).• Variable order amount.
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Periodic Review System - T=20 days
Receive 1st order
Place 1st order
Receive 2nd order
Place 2nd order
Receive 3rd order
Place 3rd order
LT1 LT2 LT3
Each increase in inventory is size M-amount on hand.(M=90 in this example.)
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INV
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Periodic Review System - T=20 days
Receive 1st order
Place 1st order
Receive 2nd order
Place 2nd order
Receive 3rd order
Place 3rd order
LT1 LT2 LT3
Time between 1st & 2nd order
(20 days)
Time between 2nd & 3rd order
(20 days)
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Optimal Inventory Control
• For perpetual (continual) demand.
• Treat each stocking point independently.
• Consider 1 product art 1 location.
Reorder Periodic
Determine: Point System Review System
How much to order: Q M-qi
When to (re)order: ROP T
Find optimal values for: Q & ROP or for M & T.
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D = demand (usually annual) d = demand rateS = order cost ($/order) LT = (average) lead timeI = carrying cost k = stockout cost
(% of value/unit time) P = probability of being inC = item value ($/item) stock during lead time
sd = std. deviation of demandsLT = std. deviation of lead times’d = std. deviation of demand during lead time
Q = order quantity N = number of orders/yearTC = total cost (usually annual)ROP = reorder pointT = time between orders
Inventory Variables
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No variability in demand and lead time (sd = 0, sLT = 0).Will never have a stock out.
Simplest Case - Constant demand and lead time
Invento
ry
Time
ROPQ
Suppose: d = 4/day and LT = 3 days
Then ROP = 12 (ROP = d x LT)
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Constant demand and lead timeIn
vento
ry
Time
ROPQ
TC = Order cost + Inventory carrying cost
Order cost = N x S = (D/Q) x S
Carrying cost = Average inventory level x C x I
= (Q/2) x C x I
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Economic Order Quantity (EOQ)In
vento
ry
Time
ROPQ
Select Q to minimize total cost.
Set derivative of TC with respect to Q equal to zero.
TC = QD S + IC 2
Q
0 = -Q2
D S +2IC
Q =IC
2DS
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Optimal OrderingIn
vento
ry
Time
ROPQ
Economic order quantity:
Optimal number of orders/year:
Optimal time between orders:
Optimal cost:
TC = Q*D S + IC 2
Q*
2DSQ* =
IC
Q*D
DQ*
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Example
D = 10,000/yearS = $61.25/orderI = 20%/yearC = $50/item
TC = Q*D S + IC 2
Q*
2DSQ* =
IC = 2(10,000)(61.25)(0.2)(50)
= 350 units/order
=10,000
350(61.25) + (0.2)(50)
3502
= 1750 + 1750 = $3500/year
N = 10,000350
= 28.57 orders/year
T = 35010,000
= 0.035 years = 1.82 weeks
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Example - continuedQ* = 350 units/orderN = 28.57 orders/yearT = 1.82 weeks
This is not a very convenient schedule for ordering!
Suppose you order every 2 weeks:T = 2 weeks, so N = 26 orders/year
TC = QD S + IC 2
Q =10,000384.6
(61.25) + (0.2)(50)384.6
2
= 1592.56 + 1923.00 = $3515.56/year
Q =DN
= 384.6 units/order (10% over EOQ)10,000
26=
Q = 384.6 is 9.9% over EOQ, but TC is only 0.4% over optimal cost!!!
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0
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2000
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5000
6000
100 200 300 400 500 600 700
Q
Cost
Total Cost
Carrying Cost
Order Cost
Model is Robust
Q* = 350 TC = $3500/year
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Model is Robust
Changing Q by 20% increases cost by a few percent.
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Cost
Carrying Cost
Order Cost
Total Cost
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Model is Robust
• A small change in Q (or N or T) causes very little increase in the total cost.– Changing Q by 10% increases cost < 1%.– Changing Q changes N=D/Q, T=Q/D and TC.– Changing N or T changes Q!
• A near optimal order plan, will have a very near optimal cost.
• You can adjust values to fit business operations.– Order every other week vs. every 1.82 weeks.– Order in multiples of 100 if required rather than Q*.
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Non-instantaneous Resupply
• Produce several products on same equipment.
• Consider one product.
p = production rate (for example, units/day)
d = demand rate (for example, units/day)
• Inventory increases slowly while it is produced.
• Inventory decreases once production stops.
• Stop producing this product when inventory is “large enough”.
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Inventory Level
Suppose: p = 10/day (while producing this product).
d = 3/day (for this product).
Put p-d = 7 in inventory every day while producing.
Remove d = 3 from inventory every day while not producing this product.
Invento
ry
Time
Produce Q Do not produce
Slope=7Slope=-3
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D = demand (usually annual) d = demand rateS = setup cost ($/setup) p = production rateI = carrying cost
(% of value/unit time)C = item value ($/item)
Assume d and p are constant (no variability).
Q = production quantity (in each production run) N = number of production runs (setups)/yearTC = total cost (usually annual)
Also want: Length of a production run (for example, in days)Length of time between runs (cycle time)
Variables
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Inventory LevelIn
vento
ry
Time
Maximuminventory
Inventory pattern repeats:Produce Q units of product of interest.Then produce other products.
Every production run of Q units requires 1 setup.Find Q to minimize total cost.
Produce Q Do not produce
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Inventory LevelIn
vento
ry
Time
Maximuminventory
TC = Setup cost + Inventory carrying cost
Setup cost = N x S = (D/Q) x S
Carrying cost = Average inventory level x C x I
= (Max. inventory/2) x C x I
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Maximum Inventory LevelIn
vento
ry
Time
Maximuminventory
Length of a production run = Q/p (days)
Max. inventory = (p-d) x Q/p = Q
Carrying cost = IC
p-dp
p-dp
Q2
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Optimum Production Run Size: QIn
vento
ry
Time
Maximuminventory
TC = QD S + IC 2
Q
Q =IC
2DS
Select Q to minimize total cost.
Set derivative of TC with respect to Q equal to zero.
p-dp
p-dp
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Non-instantaneous Resupply Equations
TC = QD S + IC 2
Q p-dp
Q =IC
2DSp-dp
N = D/Q
Length of a production run = Q/p
Length of time between runs = Q/d
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Non-instantaneous Resupply Example
TC = 63,246 + 63,246 = $126,492/year
Every 7.91 days begin a 2.64 day production run.
Q =0.2x6000
2x5000x2000
60-2060
Q/p = 158.11/60 = 2.64 days
Q/d = 158.11/20 = 7.91 days
D=5000/year assume 250 days/yearI = 20%/yearS = $2000/setupC = $6000/unit p=60/day
First, calculate d=5000/250 = 20/day
= 158.11 units
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Adjust Values to Fit Business Cycles
Change cycle length to 8 days -> Q/d = 8 days
Then: Q = 160 unitsQ/p = 2.67 daysTC = 62,500 + 64,000 = $126,500/year
8 16 240
Production runs
Produce other products
2.7 10.7 18.7
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Cost is Insensitive to Small Changes
Change cycle length to 10 days=2 weeks (+26%)
Then: Q/d = 10 daysQ = 200 units Q/p = 3.33 daysTC = 50,000 + 80,000 = $130,000/year
TC is only 2.8% over minimum TC!
10 200
Production runs
Produce other products
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Scheduling Multiple Products
Suppose 3 products are produced on the same equipment.Optimal values are:
P1: Q/d = 7.9 1 Q/p = 2.64
P2: Q/d = 13.4 Q/p = 4.8
P2: Q/d = 25.8 Q/p = 5.9
Adjust cycle lengths to a common value or multiple.
For example 8 days
P1: Q/d = 8 -> Q/p = 2.7
P2: Q/d = 12 -> Q/p = 4.3
P2: Q/d = 24 -> Q/p = 5.5
Now schedule 3 runs of P1, 2 runs of P2 and 1 run of P3 every 24 days.
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Scheduling Multiple Products - continued
P1: Q/d = 8 -> Q/p = 2.7
P2: Q/d = 12 -> Q/p = 4.3
P2: Q/d = 24 -> Q/p = 5.5
Now schedule 3 runs of P1, 2 runs of P2 and 1 run of P3 every 24 days.
P1
P2
P3
Idle
2.70 7 9.7 15.2 17.9 22.2 24
P1 P1 P1P2 P2P3
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Reorder Point System - Variability
Order amount Q when inventory falls to level ROP.
If demand or lead time are larger than expected -> stockout
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90
Time (day)
INV
EN
TO
RY
ROP Inventory Level
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Variability
Variability in demand and lead time may cause stockouts.
d = mean demandsd = std. deviation of demand
LT = mean lead timesLT = std. deviation of lead time
s’d = std. deviation of demand during lead time
LT x sd2 + d2 x sLT
2s’d =
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Safety Stock
Use safety stock to protect against stockouts when demand or lead time is not constant.
Safety stock = z x s’d
z is from Standard Normal Distribution Table and is based on P = Probability of being in-stock during lead time.
ROP = expected demand during lead time + safety stock
= d x LT + z x s’d
Average Inventory Level (AIL) = regular stock + safety stockAIL =
2Q
+ z x s’d
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Special Cases
1. Constant lead time, variable demand: sLT = 0
2. Constant demand, variable lead time: sd = 0
3. Constant demand, constant lead time: sd = 0, sLT = 0
LT x sd2 s’d = = sd LT
d2 x sLT2s’d = = dsLT
s’d = 0
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Total Cost
TC = Order cost + Regular stock carrying cost
+ Safety stock carrying cost + Stockout cost
TC = QD S + IC 2
Q + ICz s’d +
QD k s’d E(z)
k = out-of-stock cost per unit short
s’d E(z) = expected number of units out-of-stock in one order cycle
E(z) = unit Normal loss integral
P -> z (from Appendix A) -> E(z) (from Appendix B)
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3 Cases
1. Stockout cost k is known; P is not known.
-> Calculate optimal P by repeating (1) and (2) until z does not change.
2. Stock cost k is not known; P is known.-> Can not use last term in TC.
3. Stockout cost k is known; P is known.-> Could use k to calculate optimal P.
P = 1 - Dk
QIC(1)
Q = IC2D[s + ks’dE(z)
(2)
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Reorder Point Example
D = 5000 units/year d = 96.15 units/weekS = $10/order sd = 10 units/week
C = $5/unitI = 20% per yearLT = 2 weeks (constant) sLT = 0
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Reorder Point Example - Case 1
D = 5000 units/year d = 96.15 units/weekS = $10/order sd = 10 units/week
C = $5/unitI = 20% per yearLT = 2 weeks (constant) sLT = 0
• k = $2/unit; P is not given
• Iterate to find optimal P.
Q =0.2x5
2x5000x10 = 316.23 units
s’d = sd LT = 14.14= 10 2
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Case 1 (continued) - Find best P
P = 1 - 5000(2)
316.23(0.2)5
Q = 0.2(5)2(5000)[10 + 2(14.14)0.0123
= 0.9684
z = 1.86 E(z) = 0.0123
= 321.68
P = 1 - 5000(2)
321.68(0.2)5
Q = 0.2(5)2(5000)[10 + 2(14.14)0.0126
= 0.9678
z = 1.85 E(z) = 0.0126
= 321.81
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Case 1 (continued)
P = 1 - 5000(2)
321.81(0.2)5= 0.9678
z = 1.85 E(z) = 0.0126
• z does not change, so STOP
Solution: Q = 322 z = 1.85 E(z) = 0.0126
TC = 155.28 + 161.00 + 26.16 + 5.53 = $347.97/year
ROP = d x LT + z x s’d = 96.15(2) + 1.85(14.14) = 218.46
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Reorder Point Example - Case 2
D = 5000 units/year d = 96.15 units/weekS = $10/order sd = 10 units/week
C = $5/unitI = 20% per yearLT = 2 weeks (constant) sLT = 0
• k is not known; P =90%
Q =0.2x5
2x5000x10 = 316.23 units s’d = 14.14 (as in Case 1)
Solution: z = 1.28
TC = 158.23 + 158.00 + 18.10 = $334.33/year
ROP = d x LT + z x s’d = 96.15(2) + 1.28(14.14) = 210.40
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Reorder Point Example - Case 3
D = 5000 units/year d = 96.15 units/weekS = $10/order sd = 10 units/week
C = $5/unitI = 20% per yearLT = 2 weeks (constant) sLT = 0
• k =$2/unit; P =90%
Q =0.2x5
2x5000x10 = 316.23 units s’d = 14.14 (as in Case 2)
Solution: z = 1.28
TC = 158.23 + 158.00 + 18.10 + 21.25 = $355.58/year
ROP = d x LT + z x s’d = 96.15(2) + 1.28(14.14) = 210.40
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Reorder Point Example - Case 3
• k =$2/unit; P =90%
Q = 316.23Solution:
TC = $355.58/year
ROP = 210.40
• Could use k=$2/unit to find optimal P
• It would be P = 96.78% as in Case 1!
• Order size would be slightly larger (322 vs. 316).
• Cost would be slightly less ($347.97 vs. $355.58).
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Reorder Point Example - Case 4
• Suppose we keep no safety stock
Q =0.2x5
2x5000x10 = 316.23 units
Solution:
TC = 158.23 + 158.00 + 0 + 178.50 = $494.73/year
ROP = d x LT = 96.15(2) = 192.30
• With no safety stock there is a stockout whenever demand during lead time exceeds expected amount (dxLT).
• Therefore: P = 0.5
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Reorder Point Example - Summary
Case k P Q ROP TC($/year)
1 2 .9678 322 218 347.97
2 - .90 316 210 334.33
3 2 .90 316 210 355.58
4 2 .50 316 192 494.73
• A small amount of safety stock can save a large amount!– Case 4 vs Case 3
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P and SL
• Suppose that on average:– There are 10 orders/year.– Each order is for 100 items (Q=100).– We are out-of-stock 2 items per year on one order.
P = probability of being in stock during lead time. = 1 - probability of being our-of-stock during lead time.
= 1 - 1/10 = 0.90
SL= Service level = % of items in-stock = 1 - % of items out-of-stock = 1 - 2/1000 = 0.998
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Expected number of units out-of-stock/year
Service Level - Reorder Point
Annual demand
SL= 1 - % of items out-of-stock
= 1 -
(D/Q) x s’d x E(z)
D= 1 -
s’d E(z)
Q= 1 -
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Service Levels for Cases 1-4
Case 1: SL = 1 -
Case 2: SL = 1 -
Case 3: SL = 1 -
Case 4: SL = 1 -
14.14(.0126)322
= 0.9994
14.14(.0475)316
= 0.9979
14.14(.0475)316
= 0.9979
14.14(.3989)316
= 0.9822
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Reorder Point Example - Summary
Case k P Q ROP TC($/yr) SL
1 2 .9678 322 218 347.97 .9994
2 - .90 316 210 334.33 .9979
3 2 .90 316 210 355.58 .9979
4 2 .50 316 192 494.73 .9822
• Note difference between P and SL!
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Out-of-Stock for Cases 1-4
Case 1: Out-of-stock: 3 items per year and 0.5 orders/year
SL = 0.9994 -> (1-.9994)x5000 = 3 items/yearP = 0.9678 -> (1-.9678)x5000/322 = 0.5 orders/year
Case 2 & 3: Out-of-stock: 10.5 items per year and 1.58 orders/year
SL = 0.9979 -> (1-.9979)x5000 = 10.5 items/yearP = 0.90 -> (1-.90)x5000/316 = 1.58 orders/year
Case 4: Out-of-stock: 89 items per year and 7.9 orders/year
SL = 0.98229 -> (1-.9822)x5000 = 89 items/yearP = 0.50 -> (1-.50)x5000/316 = 7.9 orders/year
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Lead Time Variability in Example
D = 5000 units/year d = 96.15 units/weekS = $10/order sd = 10 units/week
C = $5/unitI = 20% per yearLT = 2 weeks (constant)
Suppose sLT = 1.2 (not 0 as before)
Now:
For constant lead time (sLT = 0) s’d =14.14
Additional safety stock due to lead time variability = z(116.24-14.14)
LT x sd2 + d2 x sLT
2s’d = = 116.24
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Optimal Inventory Control
• For perpetual (continual) demand.
• Treat each stocking point independently.
• Consider 1 product art 1 location.
Reorder
Determine: Point System
How much to order: Q
When to (re)order: ROP