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Problem 1:
Historical demand for a product is

                             DEMAND
January                       12
February                      11
March                         15
April                            12
May                            16
June                            15

a. Using a weighted moving average with weights of 0.60, 0.30, and 0.10, find the July forecast.
b. Using a simple three-month moving average, find the July forecast.
c. Using single exponential smoothing with α = 0.2 and a June forecast = 13, find the July forecast. Make whatever assumptions you wish.
d. Using simple linear regression analysis, calculate the regression equation for the preceding demand data.
e. Using the regression equation in d, calculate the forecast for July.

Problem2:

Harlen Industries has a simple forecasting model: Take the actual demand for the same month last year and divide that by the number of fractional weeks in that month. This gives the average weekly demand for that month. This weekly average is used as the weekly forecast for the same month this year. This technique was used to forecast eight weeks for this year, which are shown below along with the actual demand that occurred. The following eight weeks show the forecast (based on last year) and the demand that actually occurred:

WEEK                           FORECAST DEMAND                   ACTUAL DEMAND 

1                                            140                                                   137 
2                                            140                                                   133 
3                                            140                                                   150 
4                                            140                                                   160 
5                                            140                                                   180 
6                                            150                                                   170 
7                                            150                                                   185 
8                                            150                                                   205

a. Compute the MAD of forecast errors.
b. Using the RSFE, compute the tracking signal.
c. Based on your answers to a and b, comment on Harlen's method of forecasting.

Problem 3:
Tucson Machinery, Ins., manufactures numerically controlled machines, which sell for an average price of $0.5 million each. Sales for these NCM's for the past two years were as follows:

Quarter                   Quantity (units)
last year 
I                                      12 
II                                     18 
III                                    26 
IV                                    16 
Quarter Quantity 
This year
I                                      16 
II                                     24 
III                                    28 
IV                                   18

a. Do a line using regression in Excel.
b. Find the trend and seasonal factors.
c. Forecast sales for next year.

Problem 4:

DAT, Inc., needs to develop an aggregate plan for its product line. Relevant data are:

Production time                 1 hour per unit                     beginning inventory    500 units
Average labor cost            $10 per hour                        Safety stock                One-half month. 
Workweek                          5 days, 8 hours each day   Shortage cost             $20 per unit per month. 
Days per month                 Assume 20 work days        Carrying cost               $5 per unit per month.

                                                  Per month

The forecast for next year is:
JAN.        FEB.      MAR.     APR.      MAY.   June.     July.   Aug.    Sept.     Oct.     Nov.  Dec.
2,500 3,000 4,000 3,500 3,500   3,000     3,000 4,000   4,000    4,000   3,000    3,000

Management prefers to keep a constant workforce and production level, absorbing variations in demand through inventory excesses and shortages. Demand not met is carried over to the following month.

Develop an aggregate plan that will meet the demand and other conditions of the problem. Do not try to find the optimum; just find a good solution and state the procedure you might use to test for a better solution. Make any necessary assumptions.

Operation Management, Management Studies

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