Carlos Mazur
Prof. Davood Golmohammadi
4.10. Data collected on the yearly registrations for a Six Sigma seminar at the Quality College are shown in the following table:
Year
1
2
3
4
5
6
7
8
9
10
11
Registrations
4
6
4
5
10
8
7
9
12
14
15
a) Develop a 3 year moving average to forecast registrations from year 4 to year 12.
Year
4
5
6
7
8
9
10
11
12
Forecast
4.6
5
6.3
7.6
8.3
8
9.3
11.6
13.6
b) Estimate demand again for years 4 to 12 with a 3 year weighted moving average in which registrations in the most recent years are given a weight of 2, and registrations in the other 2 years are each given a weight of 1.
Year
4
5
6
7
8
9
10
11
12
Forecast
4.5
5
7.25
7.75
8
8.25
10
12.25
14
Weights Applied
Periods
2
Previous Year
1
2/3 years ago
4
Sum of weights
c) Graph the original data and the two forecasts. Which of the two forecasting seem better?
4.18. Consider the following actual (A1) and forecast (F1) demand levels for a product:
Time Period (t)
Actual Demand (A1)
Forecast Demand (F1)
1
50
50
2
42
50
3
56
48
4
46
50
5
49
The first forecast F1 was derived by observing A1 and setting F1 equal to A1. Subsequent forecasts were derived by exponential smoothing. Using the exponential smoothing method, find the forecast time for period 5. (Hint: You need to first find the smoothing constant, α.)
To find α:
50= 50 + α(42-50)
-8α = -2 α = 0.25
F5 = 50 + 0.25(46 – 50)
F5 = 49
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