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M&L Manufacturing

GSM 5113-Operations ManagementDr Affendy Abu Hassim

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M&L Manufacturing

M&L Manufacturing makes various components for printers and

copiers. In addition to supplying these items to a major

manufacturer, the company distributes these and similar items to

office supply stores and computer stores as replacement parts for

printers and desktop copiers. In all, the company makes about 20different items. The two markets (the major manufacturer and the

replacement market) require somewhat different handling.

For example, replacement products must be packaged

individually whereas products are shipped in bulk to the majormanufacturer.

The company does not use forecasts for production planning.

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M&L Manufacturing

Because of competitive pressures and falling

profits, the manager has decided to undertake a

number of changes. One change is to introduce

more formal forecasting procedures in order toimprove production planning and inventory

management.

With that in mind, the manager wants to begin

forecasting for two products.

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M&L Manufacturing

The manager has compiled data on product demand for thetwo products from order records for the previous 14 weeks.

These are shown in the following table.

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Questions

1. What are some of the potential benefits of a more formalizedapproach to forecasting?

2. Prepare a weekly forecast for the next four weeks for eachproduct.

Briefly explain why you chose the methods you used. ( Hint:

For product 2, a simple approach, possibly some sort of naive/

intuitive approach, would be preferable to a technical approachin view of the managers disdain of more technical methods.)

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ANSWER #1.

The potential benefitof using a formalizedapproachto forecasting is that it will be easier toutilize the computer and easier to quantify theinformation.

A less formalized approachis more likely toutilize personal intuition. For small forecastingproblems, intuition may involve personal bias, whichmay be reflected in the forecast.

As the forecasting problem gets larger, it will beimpossible to rely solely on a less formalizedapproachbecause a persons intuition will be unableto process the large quantity of information.

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ANSWER #2.Product 1

Product 1Plotting the data for Product 1 reveals a linear pattern with the

exception of demand in week 7. Demand in week 7 is unusually

high and does not fit the linear trend pattern of the remaining

data. Thus, the demand for the 7th week is considered an

outlier. There are different ways of dealing with outliers. A

simple and intuitive way is to replace the demand for the week

in question with the average demand from the previous weekand the next week in the time-series. Therefore in this case, the

demand of 90 in week 7 will be replaced with 71.5= [(67 + 76)/2].

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ANSWER #2.Product 1

t Y t*Y t2

1 50 50.00 1

2 54 108.00 4

3 57 171.00 9

4 60 240.00 16

5 64 320.00 25

6 67 402.00 36

7 71.5 500.50 49

8 76 608.00 64

9 79 711.00 81

10 82 820.00 100

11 85 935.00 121

12 87 1,044.00 144

13 92 1,196.00 169

14 96 1,344.00 196

105 1,020.5 8,449.50 1,015

50.3)105()015,1(14

)5.020,1(105)50.449,8(14

)( 222

ttn

YttYnb

64.4614

)105(50.35.020,1

n

tbYa

Round b& ato two decimals:

Y= 46.64 + 3.50t

Period Forecast (T= 46.64 + 3.50t)

15 T= 46.64 + 3.50(15) = 99.14

16 T= 46.64 + 3.50(16) = 102.64

17 T= 46.64 + 3.50(17) = 106.14

18 T= 46.64 + 3.50(18) = 109.64

The next four forecasts (t= 15, 16, 17, 18) are:

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ANSWER #2 Product 2.

Product 2Plotting the data for Product 2 yields a more complex pattern:

There is a spike once every four weeks; the values between the spikes are

fairly close to each other. In addition, the data appear to be increasing at

the rate of about one unit per week. An intuitive approach would be to use

the average of the three nonspike periods plus 1.0 to predict the next threenonspike periods. Doing so for the data up to period 15 yields a very small

average forecast error (MAD = 0.54). Given the fact that we have only two

data points following the last spike, a reasonable forecast might be to use

the last three period average plus 1.0 (i.e., 43.33 to predict orders for

period 15, and use the average of the values for periods 13 and 14 plus 1.0(i.e., 43.5 + 1.0 = 44.5) as a forecast for periods 17 and 18.

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