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M&DC Purchasing & Supply Chain: Material Management

 

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Independent Demand Ordering Systems

 

Contents

  • The concept of an economic-order quantity, covered in the last chapter, addresses the question of how much to order at one time. Another important question is when to place a replacement order. If stock is not reordered soon enough, there will be a stockout and a potential loss in customer service. However, stock ordered earlier than needed will create extra inventory. The problem then is how to balance the costs o carrying extra inventory against the costs of a stockout.

  • No matter what the items are, some rules for reordering are needed and can as simple as order when needed, order every month, or order when stock falls to a pre determined level. We all use rules of some sort in our own lives, and they vary de pending on the significance of the item. A homemaker uses some intuitive rules t make up the weekly shopping list. Order enough meat for a week, order salt when th box is empty, order vanilla extract if it will be needed over the next week, and so on.

  • In industry there are many inventories that involve a large investment and when stockout costs are high. Controlling these inventories requires effective reorder systems. Three basic systems are used to determine when to order:

    • Order point system.

    • Periodic review system.

    • Material requirements planning.

  • The first two are for independent demand items; the last is for dependent demand items.

  • When the quantity of an item on hand in inventory falls to a predetermined level, called an order point, an order is placed. The quantity ordered is usually recalculated and based on economic-order-quantity concepts.

  • Using this system, an order must be placed when there is enough stock on hand to satisfy demand from the time the order is placed until the new stock arrives (called the lead time). Suppose that for a particular item the average demand is 100 units a week and the lead time is four weeks. If an order is placed when there are 400 units on hand, on the average there will be enough stock on hand to last until the new stock arrives. However, demand during any one lead-time period probably varies from the average—sometimes more and sometimes less than the 400. Statistically, half the time the demand is greater than average, and there is a stockout; half the time the demand is less than average, and there is extra stock. If it is necessary to provide some protection against a stockout, safety stock can be added. The item is ordered when the quantity on hand falls to a level equal to the demand during the lead time plus the safety stock:

OP = DDLT + SS

where

OP = order point
DDLT = demand during the lead time

SS = stock

  • It is important to note that it is the demand during the lead time that is important. The only time a stockout is possible is during the lead time. If demand during the lead time is greater than expected, there will be a stockout unless sufficient safety stock is carried.

Example Problem

  • Demand is 200 units a week, the lead time is three weeks, and safety stock is 300 units Calculate the order point.

Answer

OP = DDLT + SS

= 200 x 3 + 300 = 900 units

Figure 11.1 Quantity on hand versus time: independent demand item.

Figure 11.1 shows the relationship between safety stock, lead time, order quan­tity, and order point. With the order point system:

  • Order quantities are usually fixed.

  • The order point is determined by the average demand during the lead time. If the average demand or the lead time changes and there is no corresponding change in the order point, effectively there has been a change in safety stock.

  • The intervals between replenishment are not constant but vary depending on the actual demand during the reorder cycle.

                                             order quantity                                 Q

  • Average inventory =                         + safety stock =                + SS

                                                      2                                           2

Example Problem

  • Order quantity is 1000 units and safety stock is 300 units. What is the average annual inventory?

Answer

Average inventory =
                         

                             1000                          

                          =         + 300
                               2

                           = 800 units

  • Determining the order point depends on the demand during the lead time and the safety stock required.

  • Methods of estimating the demand during the lead time were discussed in Chapter 8. We now look at the factors to consider when determining safety stock.

 

  • Safety stock is intended to protect against uncertainty in supply and demand. Uncertainty may occur in two ways: quantity uncertainty and timing uncertainty. Quantity uncertainty occurs when the amount of supply or demand varies; for example, if the demand is greater or less than expected in a given period. Timing uncertainty occurs when the time of receipt of supply or demand differs from that expected. A customer or a supplier may change a delivery date, for instance.

  • There are two ways to protect against uncertainty: carry extra stock, called safety stock, or order early, called safety lead time. Safety stock is a calculated extra amount of stock carried and is generally used to protect against quantity uncertainty. Safety lead time is used to protect against timing uncertainty by planning order releases and order receipts earlier than required. Safety stock and safety lead time both result in extra inventory, but the methods of calculation are different.

  • Safety stock is the most common way of buffering against uncertainty and is the one described in this text. The safety stock required depends on the following:

    • Variability of demand during the lead time.

    • Frequency of reorder.

    • Service level desired.

    • Length of the lead time. The longer the lead time, the more safety stock has to be carried to provide a specified service level. This is one reason it is important to reduce lead times as much as possible.

Variation in Demand During Lead Time

  • Chapter 8 discussed forecast error and said that actual demand varies from forecast for two reasons: bias error in forecasting the average demand, and random variations in demand about the average. It is the latter with which we are concerned in determining safety stock.

  • Suppose two items, A and B, have a ten-week sales history, as shown in Figure 11.2. Average demand over the lead time of one week is 1000 per week for both items. However, the weekly demand for A has a range from 700 to 1400 units a week and that for B is from 200 to 1600 units per week. The demand for B is more erratic than that for A. If the order point is 1200 units for both items, there will be one stockout for A and four for B. If the same service level is to be provided (the same chance of stockout for all items), some method of estimating the randomness of item demand is needed

Variation in Demand About the Average

  • Suppose over the past 100 weeks a history of weekly demand for a particular iterr shows an average demand of 1000 units. As expected, most of the demands are around

Week

Item A

Item B

1 1200 400
2 1000 600
3 800 1600
4 900 1300
5 1400 200
6 1100 1100
7 1100 1500
8 700 800
9 1000 1400
10 800 1100

Total Average

10,000 10,000
1000 1000

Figure 11.2 Actual demand for two items.

  • 1000; a smaller number would be farther away from the average and still fewer would be farthest away. If the weekly demands are classified into groups or ranges about the average, a picture of the distribution of demand about the average appears. Suppose the demand is distributed as follows:

Weekly Demand

Number of Weeks

725—774

2

775—824

3

825—874

7

875—924

12

925—974

17

975—1024

20

1025—1074

17

1075—1124

12

1125—1174

7

1175—1224

3

1225—1274

2
  • These data are plotted to give the results shown in Figure 11.3. This is a histogram

Normal distribution

  • Everything in life varies—even identical twins in some respects The pattern of demand distribution about the average will differ for different product~ and markets. Some method is needed to describe the distribution—its shape, center, am spread.
    The shape of the histogram in Figure 11.3 indicates that although there is variation in the distribution, it follows a definite pattern, as shown by the smooth curve

  • Such a natural pattern shows predictability. As long as the demand conditions remain the same, we can expect the pattern to remain very much the same. If the demand i~ erratic, so is the demand pattern, making it difficult to predict with any accuracy Fortunately, most demand patterns are stable and predictable.

  • The most common predictable pattern is similar to the one outlined by the histogram in Figure 11.3 and is called a normal curve, or bell curve, because its shape resembles a bell. The shape of a perfectly normal distribution is shown in Figure 11.4.

  • The normal distribution has most of the values clustered near a central point with progressively fewer results occurring away from the center. It is symmetrical about this central point in that it spreads out evenly on both sides.

Figure 11.3 Histogram of actual demand.

Figure 11.4 Normal distribution.

  • The normal curve is described by two characteristics. One relates to its central tendency, or average, and the other to the variation, or dispersion, of the actual values about the average.

Average or mean

  • The average or mean value is at the high point of the curve. It is the central tendency of the distribution. The symbol for the mean is (pronounced “x bar”). It is calculated by adding the data and dividing by the total number of data. In mathematical terms, it can be written as:

                         X

                   X =               .

                                n

  • Where x stands for the individual data (in this case, the individual demands , (capital Greek letter sigma) is the summation sign, and n is the number of data (demands).

 

Example Problem

  • Given the following actual demands for a ten-week period, Calculate the average of the distribution.

Period

Actual Demand

1

1200

2

1000

3

800

4

900

5

1400

6

1100

7

1100

8

700

9

1000

10

800

Total

10000

Answer

                       X                1000

                   X =                 =                = 1000 units

                                 n                 10

Dispersion

  • The variation, or dispersion, of actual demands about the average refers to how closely the individual values cluster around the mean or average. It can be measured in several ways:

  • As a range of the maximum minus the minimum value.

  • As the mean absolute deviation (MAD), which is a measure of the average forecast error.

  • As a standard deviation.

 

Standard Deviation (Sigma)

  • The standard deviation is a statistical value that measures how closely the individual values cluster about the average. It is represented by the Greek letter sigma (a). The standard deviation is calculated as follows:

    1. Calculate the deviation for each period by subtracting the actual demand from the forecast demand.

    2. Square each deviation.

    3. Add the squares of the deviations.

    4. Divide the value in step 3 by the number of periods to determine the average of the squared deviations.

    5. Calculate the square root of the value calculated in step 4. This is the standard deviation.

  • It is important to note that the deviations in demand are for the same time in¬tervals as the lead time. If the lead time is one week, then the variation in demand over a one-week period is needed to determine the safety stock.

Example Problem

  • Given the data from the previous example problem, calculate the standard deviation (sigma)

Answer

Period

Forecast demand

Actual demand

Deviation

Deviation squared

1

1000

1200

200

40000

2

1000

1000

0

0

3

1000

800

—200

40000

4

1000

900

—100

10000

5

1000

1400

400

160000

6

1000

1100

100

10000

7

1000

1100

100

10000

8

1000

700

—300

90000

9

1000

1000

0

0

10

1000

800

—200

40000

Total

10000

10000

0

400000

Average of the squares of the deviation = 400,000 ± 10 40,000

From statistics, we can determine that:

The actual demand will be within ± 1 sigma of the forecast average approximately 68% of the time.
The actual demand will be within ± 2 sigma of the forecast average approximately 98% of the time.
The actual demand will be within ± 3 sigma of the forecast average approximately 99.88% of the time.
 

Determining the Safety Stock and Order Point

  • Now that we have calculated the standard deviation, we must decide how much safety stock is needed.

  • One property of the normal curve is that it is symmetrical about the average. This means that half the time the actual demand is less than the average and half the time it is greater. Safety stocks are needed to cover only those periods in which the demand during the lead time is greater than the average. Thus, a service level of 50% can be attained with no safety stock. If a higher service level is needed, safety stock must be provided to protect against those times when the actual demand is greater than the average.

  • As stated earlier, we know from statistics that the error is within ± 1 sigma of the forecast about 68% of the time (34% of the time less and 34% of the time greater than the forecast).

  • Suppose the standard deviation of demand during the lead time is 100 units and this amount is carried as safety stock. This much safety stock provides protection against stockout for the 34% of the time that actual demand is greater than expected. In total, there is enough safety stock to provide protection for the 84% of the time (50% + 34% = 84%) that a stockout is possible.

  • The service level is a statement of the percentage of time there is no stockout. But what exactly is meant by supplying the customer 84% of the time? It means being able to supply when a stockout is possible, and a stockout is possible only at the time an order is to be placed. If we order 100 times a year, there are 100 chances of a stockout. With safety stock equivalent to one mean absolute deviation, on the average we would expect no stockouts about 84 of the 100 times.

Example Problem

  • Using the figures in the last example problem in which the sigma was calculated a~ 200 units,

    1. Calculate the safety stock and the order point for an 84% service level.

    2. If a safety stock equal to two standard deviations is carried, calculate the safety stock and the order point.

Answer

  1. Safety stock = 1 sigma

                   = 1 x 200

                   = 200 units

Order point   = DDLT + SS

                   = 1000 + 200 = 1200 units

  • where DDLT and SS are as defined previously. With this order point and level of safety stock, on the average there are no stockouts 84% of the time when a stockout is possible.

    1. SS  = 2x200

                     = 400 units

               OP = DDLT + SS         

                     = 1000 + 400

                     = 1400 units

Safety factor

  • The service level is directly related to the number of standard deviations provided as safety stock and is usually called the safety factor.

  • Figure 11.5 shows safety factors for various service levels. Note that the service level is the percentage of order cycles without a stockout

Example Problem

  • If the standard deviation is 200 units, what safety stock should be carried to provide a service level of 90%? If the expected demand during the lead time is 1500 units, what is the order point?

Answer

  • From Figure 11.5, the safety factor for a service level of 90% is 1.28. Therefore,

Safety stock = sigma x safety factor

                   = 200x 1.28

                   = 256 units

   Order point = DDLT + SS

                    = 1500 + 256

                    = 1756 units

 

  • Theoretically, we want to carry enough safety stock on hand so the cost of carrying the extra inventory plus the cost of stockouts is a minimum. Stockouts cost money for the following reasons:

    • Back-order costs.

    • Lost sales.

    • Lost customers.

Service Level (%)

Safety Factor

50

0

75

0.67

80

0.84

85

1.04

90

1.28

94

1.56

95

1.65

96

1.75

97

1.88

98

2.05

99

2.33

99.86

3

99.99

4

Figure 11.5 Table of safety factors.

  • The cost of a stockout varies depending on the item, the market served, the customer, and competition. In some markets, customer service is a major competitive tool, and a stockout can be very expensive. In others, it may not be a major consideration. Stockout costs are difficult to establish. Usually the decision about what the service level should he is a senior management decision and is part of the company corporate and marketing strategy. As such, it is beyond the scope of this text.

  • The only time it is possible for a stockout to occur is when stock is running low and this happens every time an order is to be placed. Therefore, the chances of stockout are directly proportional to the frequency of reorder. The more often stock is reordered, the more often there is a chance of a stockout. Figure 11.6 shows the effect of the order quantity on the number of exposures per year. Note also that when the order quantity is increased, exposure to stockout decreases. The safety stock needed decreases, but because of the larger order quantity, the average inventor increases.

  • It is the responsibility of management to determine the number of stockout per year that are tolerable. Then the service level, safety stock, and order point can b calculated.

Figure 11.6 Exposures to stockout.

 

Example Problem

  • Suppose management stated that it could tolerate only one stockout per year for a specific item.

  • For this particular item, the annual demand is 52,000 units, it is ordered in quan¬tities of 2600, and the standard deviation of demand during the lead time is 100 units. The lead time is one week. Calculate:

    1. Number of orders per year.

    2. Service level.

    3. Safety stock.

    4. Order point.

Answer

                                                     annual demand

  1. Number of orders per year =                             
                                                  order quantity

                                                         52.000

                                                    =                =  20 times per year

                                                          2600

 

  1. Since one stockout per year is tolerable, there must be no stockouts 19 (20 — 1) times per year.

                                          20 -1

Service level =                   95%

                                          20

 

  1. From Figure 11.5

                        Safety factor = 1.65

                        Safety stock = safety factor x sigma                                       

                                           = 1.65 x 100 165 units
 

 

                                                                 (52.000)
  1. d. Demand during lead time = (1 week)               = 1000 units

                                                                      52

                                  Order point = demand during lead time + SS

                                                   = 1000 + 165 = 1165 units

 

  • Usually, there are many items in an inventory, each with different lead times. Records of actual demand and forecasts are normally made on a weekly or monthly basis for all items regardless of what the individual lead times are. It is almost impossible to measure the variation in demand about the average for each of the lead times. Some method of adjusting standard deviation for the different time intervals is needed.

  • If the lead time is zero, the standard deviation of demand is zero. As the lead time increases, the standard deviation increases. However, it will not increase in direct proportion to the increase in time. For example, if the standard deviation is 100 for a lead time of one week, then for a lead time of four weeks it will not be 400, since it is very unlikely that the deviation would be high for four weeks in a row. As the time interval increases, there is a smoothing effect, and the longer the time interval, the more smoothing takes place.

  • The following adjustment can be made to the standard deviation or the safety stock to compensate for differences between lead-time interval (LTI) and forecast interval (Fl). While not exact, the formula gives a good approximation:

 

Example Problem

  • The forecast interval is four weeks, the lead time interval is two weeks, and sigma for the forecast interval is 150 units. Calculate the standard deviation for the lead time interval.

Answer

  • The preceding relationship is also useful where there is a change in the LTI. Now it is probably more convenient to work directly with the safety stock rather than the mean absolute deviation. The relationship is as follows:

 

Example Problem

  • The safety stock for an item is 150 units, and the lead time is two weeks. If the lead time changes to three weeks, calculate the new safety stock.

Answer

                                                     = 150 x 1.22 183 units

 

  • There must be some method to show when the quantity of an item on hand has reached the order point. In practice, there are many systems, but they all are inclined to be variations or extensions of two basic systems: the two-bin system and the perpetual inventory system.

Two-Bin System

  • A quantity of an item equal to the order point quantity is set aside (frequently in a separate or second bin) and not touched until all the main stock is used up. When this stock needs to be used, the production control or purchasing department is notified and a replenishment order is placed.

  • There are variations on this system, such as the red-tag system, where a tag is placed in the stock at a point equal to the order point. Book stores frequently use this system. A tag or card is placed in a book that is in a stack in a position equivalent to the order point. When a customer takes that book to the checkout, the store is effectively notified that it is time to reorder that title.

  • The two-bin system is a simple way of keeping control of C items. Because they are of low value, it is best to spend the minimum amount of time and money controlling them. However, they do need to be managed, and someone should be assigned to ensure that when the reserve stock is reached an order must be placed. When it is out of stock, a C item becomes an A item.

Perpetual Inventory Record System

  • A perpetual inventory record is a continual account of inventory transactions as they occur. At any instant, it holds an up-to-date record of transactions. At a minimum, it contains the balance on hand, but it may also contain the quantity on order but not received, the quantity allocated but not issued, and the available balance. The accuracy of the record depends upon the speed with which transactions are recorded and the accuracy of the input. Because manual systems rely on the input of humans, they are more likely to have slow response and inaccuracies. Computer based systems have a higher transaction speed and reduce the possibility of human
    error

426254 SCREW  500

 ORDER ORDER QUANTITY POINT     100

DATE

ORDERED

RECEIVED

ISSUED

ON HAND

ALLOCATED

AVAILABLE

 

 

 

 

 

 

1

 

 

 

500

 

500

2

 

 

 

500

400

100

3

500

 

 

500

 

 

4

 

 

400

100

0

100

5

 

500

 

600

0

600

Figure 11.7 Perpetual inventory record.

  • An inventory record contains variable and permanent information. Figure 11.7 shows an example of a perpetual inventory record.

  • Permanent information is shown at the top of Figure 11.7. Although not absolutely permanent, this information does not change frequently. Any alteration is usually the result of an engineering change, manufacturing process change, or inventory management change. It includes data such as the following:

    • Part number, name, and description.

    • Storage location.

    • Order point.

    • Order quantity.

    • Lead time.

    • Safety stock.

    • Suppliers.

  • Variable information is information that changes with each transaction and in cludes the following:

    • Quantities ordered: dates, order numbers, and quantities.

    • Quantities received: dates, order numbers, and quantities.

    • Quantities issued: dates, order numbers, and quantities.

    • Balance on hand.

    • Allocated: dates, order numbers, and quantities.

    • Available balance.

  • The information depends on the needs of the company and the particular cir constancies.

 

  • In the order point system, an order is placed when the quantity on hand falls to a predetermined level called the order point. The quantity ordered is usually predetermined on some basis such as the economic-order quantity. The interval between orders varies depending on the demand during any particular cycle.

  • Using the periodic review system, the quantity on hand of a particular item is determined at specified, fixed-time intervals, and an order is placed. Figure 11.8 illustrates this system.

  • Figure 11.8 shows that the review intervals (t1, t2, and t3) are equal and that Q1, Q2’ and Q3 are not necessarily the same. Thus the review period is fixed, and the order quantity is allowed to vary. The quantity on hand plus the quantity ordered must be

  • Sufficient to last until the next shipment is received. That is, the quantity on hand plus the quantity ordered must equal the sum of the demand during the lead time plus the demand during the review period plus the safety stock.

Target Level or Maximum-Level Inventory

  • The quantity equal to the demand during the lead time plus the demand during the review period plus safety stock is called the target level or maximum-level inventory:

T=D(R+L)+ SS

where

T = target (maximum) inventory level

D = demand per unit of time

L = lead-time duration

R = review period duration

SS = safety stock

Figure 11.8 Periodic review system: units in stock versus time.

The order quantity is equal to the maximum-inventory level minus the quantity on hand at the review period:

Q= T-I

where

Q = order quantity

I = inventory on hand

The periodic review system is useful for the following:

  • Where there are many small issues from inventory, and posting transactions to inventory records are very expensive. Supermarkets and retailers are in this category.

  • Where ordering costs are small. This occurs when many different items are or­dered from one source. A regional distribution center may order most or all ol its stock from a central warehouse.

  • Where many items are ordered together to make up a production run or fill a truckload. A good example of this is a regional distribution center that orders a truckload once a week from a central warehouse.

Example Problem

  • A hardware company stocks nuts and bolts and orders them from a local supplier onc every two weeks (ten working days). Lead time is two days. The company has deter mined that the average demand for 1/2-inch bolts is 150 per week (five working days) and it wants to keep a safety stock of three days’ supply on hand. An order is to b placed this week, and stock on hand is 130 bolts.

    1. What is the target level?

    2. How many 1/2-inch bolts should be ordered this time?

Answer

Let

D = demand per unit of time = 150 ± 5 = 30 per working day

L = lead-time duration = 2 days

R = review period duration = 10 days

SS = safety stock = 3 days’ supply = 90 units

I = inventory on hand = 130 units

Then

Target level T = D(R + L) + SS

                    = 30(10 + 2) + 90

                    = 450 units

Order quantity Q = T — I

                         = 450 — 130 = 320 units

 

  • Distribution inventory includes all the finished goods held anywhere in the distribution system. The purpose of holding inventory in distribution centers is to improve customer service by locating stock near the customer and to reduce transportation costs by allowing the manufacturer to ship full loads rather than partial loads over long distances. This will be studied in Chapter 13.

  • The objectives of distribution inventory management are to provide the required level of customer service, to minimize the costs of transportation and handling, and to be able to interact with the factory to minimize scheduling problems.

  • Distribution systems vary considerably, but in general they have a central supply facility that is supported by a factory, a number of distribution centers, and, finally, customers. Figure 11.9 is a schematic of such a system. The customers may be the final consumer or some intermediary in the distribution chain.

  • Unless a firm delivers directly from factory to customer, demand on the factory is created by central supply. In turn, demand on central supply is created by the distribution centers. This can have severe repercussions on the pattern of demand on central supply and the factory. Although the demand from customers may be relatively uniform, the demand on central supply is not, because it is dependent on when the distribution centers place replenishment orders. In turn, the demand on the factory depends on when central supply places orders. Figure 11.10 shows the process schematically.

  • The distribution system is the factory’s customer, and the way the distribution system interfaces with the factory has a significant effect on the efficiency of factory operations.

  • Distribution inventory management systems can be classified into decentralized, centralized and distribution requirements planning.

Decentralized System

  • In a decentralized system, each distribution center first determines what it needs and when, and then places orders on central supply. Each center orders on its own without regard for the needs of other centers, available inventory at central supply, or the production schedule of the factory.

  • The advantage of the decentralized system is that each center can operate on its own and thus reduce communication and coordination expense. The disadvantage is the lack of coordination and the effect this may have on inventories, customer service, and factory schedules. Because of these deficiencies, many distribution systems have moved toward more central control.

  • A number of ordering systems can be used, including the order point and periodic review systems. The decentralized system is sometimes called the pull system because orders are placed on central supply and “pulled” through the system.

Figure 11.9 Schematic of a distribution system.

Figure 11.10 Distribution inventory.

Centralized System

  • In a centralized system, all forecasting and order decisions are made centrally. Stock is “pushed” out into the system from central supply. Distribution centers have no say about what they receive.

  • Different ordering systems can be used, but generally an attempt is made to replace the stock that has been sold and to provide for special situations such as seasonality or sales promotions. These systems attempt to balance the available inventory with the needs of each distribution center.

  • The advantage of these systems is the coordination between factory, central supply, and distribution center needs. The disadvantage is the inability to react to local demand, thus lowering the level of service.

Distribution Requirements Planning

  • Distribution requirements planning are a system that forecasts when the various demands will be made by the system on central supply. This gives central supply and the factory the opportunity to plan for the goods that will actually be needed and when. it is able both to respond to customer demand and coordinate planning and control.

  • The system translates the logic of material requirements planning to the distribution system. Planned order releases from the various distribution centers became the input to the material plan of central supply. The planned order releases from central supply become the forecast of demand for the factory master production schedule Figure 11.11 shows the system schematically. The records shown are all for the same part number.

Figure 11.11 Distribution requirements planning.

Example Problem

  • A company making lawnmowers has a central supply attached to their factory and two distribution centers. Distribution center A forecasts demand at 25, 30, 55, 50, and 30 units over the next five weeks and has 100 lawnmowers in transit that are due in week 2. The transit time is two weeks, the order quantity is 100 units, and there are 50 units on hand. Distribution center B forecasts demand at 95, 85, 100, 70, and 50 over the next five weeks. Transit time is one week, the order quantity is 200 units, and there are 100 units on hand. Calculate the gross requirements, projected available, and planned order releases for the two distribution centers, and the gross requirements, projected available, and planned order releases for the central warehouse.

Answer

Distribution Center A

Transit Time: 2 weeks

Order Quantity: 100 units

Week

1

2

3

4

5

Gross Requirements

25

30

55

50

30

In Transit

 

100

 

 

 

Projected Available 50

25

95

40

90

60

Planned Order Release

 

100

 

 

 

Distribution Center B

Transit Time:I week

Order Quantity: 200 units

Week

1

2

3

4

5

Gross Requirements

95

85

100

70

30

In Transit

 

 

 

 

 

Projected Available 100

2

120

20

150

100

Planned Order Release

 200

 

 200

 

 

Central Supply

Lead Time: 2 weeks

Order Quantity: 500 units

Week

1

2

3

4

5

Gross Requirements

200

100

200

   

In Transit

 

 

 

   

Projected Available 100

200

100

400

   

Planned Order Release

500