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12 – 1 Inventory Management © 2006 Prentice Hall, Inc.

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Presentation on theme: "12 – 1 Inventory Management © 2006 Prentice Hall, Inc."— Presentation transcript:

1 12 – 1 Inventory Management © 2006 Prentice Hall, Inc.

2 12 – 2 Inventory  One of the most expensive assets of many companies representing as much as 50% of total invested capital  Operations managers must balance inventory investment and customer service

3 12 – 3 Functions of Inventory 1.To decouple or separate various parts of the production process 2.To decouple the firm from fluctuations in demand and provide a stock of goods that will provide a selection for customers 3.To take advantage of quantity discounts 4.To hedge against inflation

4 12 – 4 Types of Inventory  Raw material  Purchased but not processed  Work-in-process  Undergone some change but not completed  A function of cycle time for a product  Maintenance/repair/operating (MRO)  Necessary to keep machinery and processes productive  Finished goods  Completed product awaiting shipment

5 12 – 5 The Material Flow Cycle InputWait forWait toMoveWait in queueSetupRunOutput inspectionbe movedtimefor operatortimetime Cycle time 95%5%

6 12 – 6 Inventory Management  How inventory items can be classified  How accurate inventory records can be maintained

7 12 – 7 ABC Analysis  Divides inventory into three classes based on annual dollar volume  Class A - high annual dollar volume  Class B - medium annual dollar volume  Class C - low annual dollar volume  Used to establish policies that focus on the few critical parts and not the many trivial ones

8 12 – 8 ABC Analysis Item Stock Number Percent of Number of Items Stocked Annual Volume (units) x Unit Cost = Annual Dollar Volume Percent of Annual Dollar Volume Class #1028620%1,000 $ 90.00 $ 90,000 38.8%72%A #11526500154.0077,00033.2%A #127601,55017.0026,35011.3%B #1086730%35042.8615,0016.4%23%B #105001,00012.5012,5005.4%B

9 12 – 9 ABC Analysis Item Stock Number Percent of Number of Items Stocked Annual Volume (units) x Unit Cost = Annual Dollar Volume Percent of Annual Dollar Volume Class #12572600 $ 14.17 $ 8,502 3.7%C #140752,000.601,200.5%C #0103650%1008.50850.4%C #013071,200.42504.2%C #10572250.60150.1%C

10 12 – 10 ABC Analysis A Items B Items C Items Percent of annual dollar usage 80 80 – 70 70 – 60 60 – 50 50 – 40 40 – 30 30 – 20 20 – 10 10 – 0 0 – |||||||||| 102030405060708090100 Percent of inventory items

11 12 – 11 ABC Analysis  Other criteria than annual dollar volume may be used  Anticipated engineering changes  Delivery problems  Quality problems  High unit cost

12 12 – 12 ABC Analysis  Policies employed may include  More emphasis on supplier development for A items  Tighter physical inventory control for A items  More care in forecasting A items

13 12 – 13 Record Accuracy  Accurate records are a critical ingredient in production and inventory systems  Allows organization to focus on what is needed  Necessary to make precise decisions about ordering, scheduling, and shipping  Incoming and outgoing record keeping must be accurate  Stockrooms should be secure

14 12 – 14 Cycle Counting  Items are counted and records updated on a periodic basis  Often used with ABC analysis to determine cycle  Has several advantages  Eliminates shutdowns and interruptions  Eliminates annual inventory adjustment  Trained personnel audit inventory accuracy  Allows causes of errors to be identified and corrected  Maintains accurate inventory records

15 12 – 15 Cycle Counting Example 5,000 items in inventory, 500 A items, 1,750 B items, 2,750 C items Policy is to count A items every month (20 working days), B items every quarter (60 days), and C items every six months (120 days) Item Class Quantity Cycle Counting Policy Number of Items Counted per Day A500 Each month 500/20 = 25/day B1,750 Each quarter 1,750/60 = 29/day C2,750 Every 6 months 2,750/120 = 23/day 77/day

16 12 – 16 Independent Versus Dependent Demand  Independent demand - the demand for item is independent of the demand for any other item in inventory  Dependent demand - the demand for item is dependent upon the demand for some other item in the inventory

17 12 – 17 Holding, Ordering, and Setup Costs  Holding costs - the costs of holding or “carrying” inventory over time  Ordering costs - the costs of placing an order and receiving goods  Setup costs - cost to prepare a machine or process for manufacturing an order

18 12 – 18 Holding Costs Category Cost (and Range) as a Percent of Inventory Valu e Housing costs (including rent or depreciation, operating costs, taxes, insurance) 6% (3 - 10%) Material handling costs (equipment lease or depreciation, power, operating cost) 3% (1 - 3.5%) Labor cost 3% (3 - 5%) Investment costs (borrowing costs, taxes, and insurance on inventory) 11% (6 - 24%) Pilferage, space, and obsolescence 3% (2 - 5%) Overall carrying cost 26%

19 12 – 19 Inventory Models for Independent Demand  Basic economic order quantity  Production order quantity  Quantity discount model Need to determine when and how much to order

20 12 – 20 Basic EOQ Model 1.Demand is known, constant, and independent 2.Lead time is known and constant 3.Receipt of inventory is instantaneous and complete 4.Quantity discounts are not possible 5.Only variable costs are setup and holding 6.Stockouts can be completely avoided Important assumptions

21 12 – 21 Inventory Usage Over Time Order quantity = Q (maximum inventory level) Inventory level Time Usage rate Average inventory on hand Q2 Minimum inventory

22 12 – 22 Minimizing Costs Objective is to minimize total costs Annual cost Order quantity Curve for total cost of holding and setup Holding cost curve Setup (or order) cost curve Minimum total cost Optimal order quantity

23 12 – 23 The EOQ Model Q= Number of pieces per order Q*= Optimal number of pieces per order (EOQ) D= Annual demand in units for the Inventory item S= Setup or ordering cost for each order H= Holding or carrying cost per unit per year Annual setup cost =(Number of orders placed per year) x (Setup or order cost per order) Annual demand Number of units in each order Setup or order cost per order = = (S) DQ Annual setup cost = S DQDQ

24 12 – 24 The EOQ Model Q= Number of pieces per order Q*= Optimal number of pieces per order (EOQ) D= Annual demand in units for the Inventory item S= Setup or ordering cost for each order H= Holding or carrying cost per unit per year Annual holding cost =(Average inventory level) x (Holding cost per unit per year) Order quantity 2 = (Holding cost per unit per year) = (H) Q2 Annual setup cost = S DQDQ Annual holding cost = H Q2Q2

25 12 – 25 The EOQ Model Q= Number of pieces per order Q*= Optimal number of pieces per order (EOQ) D= Annual demand in units for the Inventory item S= Setup or ordering cost for each order H= Holding or carrying cost per unit per year Optimal order quantity is found when annual setup cost equals annual holding cost Annual setup cost = S DQDQ Annual holding cost = H Q2Q2 DQ S = H Q2 Solving for Q* 2DS = Q 2 H Q 2 = 2DS/H Q* = 2DS/H

26 12 – 26 An EOQ Example Determine optimal number of needles to order D = 1,000 units S = $10 per order H = $.50 per unit per year Q* = 2DS H Q* = 2(1,000)(10)0.50 = 40,000 = 200 units

27 12 – 27 An EOQ Example Determine optimal number of needles to order D = 1,000 units Q*= 200 units S = $10 per order H = $.50 per unit per year = N = = Expected number of orders Demand Order quantity DQ* N = = 5 orders per year 1,000200

28 12 – 28 An EOQ Example Determine optimal number of needles to order D = 1,000 unitsQ*= 200 units S = $10 per orderN= 5 orders per year H = $.50 per unit per year = T = Expected time between orders Number of working days per year N T = = 50 days between orders 2505

29 12 – 29 An EOQ Example Determine optimal number of needles to order D = 1,000 unitsQ*= 200 units S = $10 per orderN= 5 orders per year H = $.50 per unit per yearT= 50 days Total annual cost = Setup cost + Holding cost TC = S + H DQQ2 TC = ($10) + ($.50) 1,0002002002 TC = (5)($10) + (100)($.50) = $50 + $50 = $100

30 12 – 30 Robust Model  The EOQ model is robust  It works even if all parameters and assumptions are not met  The total cost curve is relatively flat in the area of the EOQ

31 12 – 31 An EOQ Example Management underestimated demand by 50% D = 1,000 units Q*= 200 units S = $10 per orderN= 5 orders per year H = $.50 per unit per yearT= 50 days TC = S + H DQQ2 TC = ($10) + ($.50) = $75 + $50 = $125 1,5002002002 1,500 units Total annual cost increases by only 25%

32 12 – 32 An EOQ Example Actual EOQ for new demand is 244.9 units D = 1,000 units Q*= 244.9 units S = $10 per orderN= 5 orders per year H = $.50 per unit per yearT= 50 days TC = S + H DQQ2 TC = ($10) + ($.50) 1,500244.9244.92 1,500 units TC = $61.24 + $61.24 = $122.48 Only 2% less than the total cost of $125 when the order quantity was 200

33 12 – 33 Reorder Points  EOQ answers the “how much” question  The reorder point (ROP) tells when to order ROP = Lead time for a new order in days Demand per day = d x L d = D Number of working days in a year

34 12 – 34 Reorder Point Curve Q* ROP (units) Inventory level (units) Time (days) Lead time = L Slope = units/day = d

35 12 – 35 Reorder Point Example Demand = 8,000 DVDs per year 250 working day year Lead time for orders is 3 working days ROP = d x L d = D Number of working days in a year = 8,000/250 = 32 units = 32 units per day x 3 days = 96 units

36 12 – 36 Production Order Quantity Model  Used when inventory builds up over a period of time after an order is placed  Used when units are produced and sold simultaneously

37 12 – 37 Production Order Quantity Model Inventory level Time Demand part of cycle with no production Part of inventory cycle during which production (and usage) is taking place t Maximum inventory

38 12 – 38 Production Order Quantity Model Q =Number of pieces per order p =Daily production rate H =Holding cost per unit per year d =Daily demand/usage rate t =Length of the production run in days = (Average inventory level) x Annual inventory holding cost Holding cost per unit per year = (Maximum inventory level)/2 Annual inventory level = – Maximum inventory level Total produced during the production run Total used during the production run = pt – dt

39 12 – 39 Production Order Quantity Model Q =Number of pieces per order p =Daily production rate H =Holding cost per unit per year d =Daily demand/usage rate t =Length of the production run in days = – Maximum inventory level Total produced during the production run Total used during the production run = pt – dt However, Q = total produced = pt ; thus t = Q/p Maximum inventory level = p – d = Q 1 – QpQpdp Holding cost = (H) = 1 – H dpQ2 Maximum inventory level 2

40 12 – 40 Production Order Quantity Model Q =Number of pieces per order p =Daily production rate H =Holding cost per unit per year d =Daily demand/usage rate D =Annual demand Setup cost =(D/Q)S Holding cost =1/2 HQ[1 - (d/p)] (D/Q)S = 1/2 HQ[1 - (d/p)] Q2 =Q2 =Q2 =Q2 = 2DS H[1 - (d/p)] Q* = 2DS H[1 - (d/p)]

41 12 – 41 Production Order Quantity Example D =1,000 units p =8 units per day S =$10 d =4 units per day H =$0.50 per unit per year Q* = 2DS H[1 - (d/p)] = 282.8 or 283 hubcaps Q* = = 80,000 2(1,000)(10) 0.50[1 - (4/8)]

42 12 – 42 Production Order Quantity Model When annual data are used the equation becomes Q* = 2DS annual demand rate annual production rate H 1 –

43 12 – 43 Probabilistic Models and Safety Stock  Used when demand is not constant or certain  Use safety stock to achieve a desired service level and avoid stockouts ROP = d x L + ss Annual stockout costs = the sum of the units short x the probability x the stockout cost/unit x the number of orders per year

44 12 – 44 Safety stock16.5 units ROP  Place order Probabilistic Demand Inventory level Time 0 Minimum demand during lead time Maximum demand during lead time Mean demand during lead time Normal distribution probability of demand during lead time Expected demand during lead time (350 kits) ROP = 350 + safety stock of 16.5 = 366.5 Receive order Lead time

45 12 – 45 Probabilistic Demand Safety stock Probability of no stockout 95% of the time Mean demand 350 ROP = ? kits Quantity Number of standard deviations 0 z Risk of a stockout (5% of area of normal curve)

46 12 – 46 Probabilistic Demand Use prescribed service levels to set safety stock when the cost of stockouts cannot be determined ROP = demand during lead time + Z  dlt whereZ =number of standard deviations  dlt =standard deviation of demand during lead time

47 12 – 47 EOQ Fallacies Unit Price always fixedUnit Price always fixed All resources related to inventory are sufficientAll resources related to inventory are sufficient Order can be fractionalizedOrder can be fractionalized Unrealistic assumptionsUnrealistic assumptions Items are IndependentItems are Independent Storage Policy is assumed to be randomizedStorage Policy is assumed to be randomized

48 12 – 48 Multiple (independent) items Total cost of n itemsTotal cost of n items EOQ for a single itemEOQ for a single item The same model can be used for each itemThe same model can be used for each item

49 12 – 49 Multiple (dependent) items Assume that each unit of item i requires f i square feet of storage space and the total of F square feet is availableAssume that each unit of item i requires f i square feet of storage space and the total of F square feet is available The EOQ Model is then subjected toThe EOQ Model is then subjected to

50 12 – 50 Multiple (dependent) items The Order quantity for each item i can be found by applying the Lagrangian Relaxation : L functionThe Order quantity for each item i can be found by applying the Lagrangian Relaxation : L function

51 12 – 51 Multiple (dependent) items EOQ for each single item can be found fromEOQ for each single item can be found from Then,Then,

52 12 – 52 Multiple (dependent) items To find all Q i ’s that satisfy the constraint of storage space F, the search for appropriate value of is requiredTo find all Q i ’s that satisfy the constraint of storage space F, the search for appropriate value of is required


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