In: Statistics and Probability
Franklin Tooling, Inc., manufactures specialty tooling for firms in the paper-making industry. All of their products are engineer-to-order and so the company never knows exactly what components to purchase for a tool until a customer places an order. However, the company believes that weekly demand for a few components is fairly stable. Component 135.AG is one such item. The last 26 weeks of historical use of component 135.AG is recorded below.
Week |
Demand |
Week |
Demand |
1 |
137 |
14 |
131 |
2 |
136 |
15 |
132 |
3 |
143 |
16 |
124 |
4 |
136 |
17 |
121 |
5 |
141 |
18 |
127 |
6 |
128 |
19 |
118 |
7 |
149 |
20 |
120 |
8 |
138 |
21 |
115 |
9 |
134 |
22 |
106 |
10 |
142 |
23 |
120 |
11 |
125 |
24 |
113 |
12 |
134 |
25 |
121 |
13 |
118 |
26 |
119 |
Use OM Explorer’s Time Series Forecasting Solver to evaluate the following forecasting methods. Start error measurement in the fifth week, so all methods are evaluated over the same time interval. Use the default settings for initial forecasts.
Soln
i)
3-Period Moving Average = (Sum of Previous 3 Periods Value)/3
MAD = Average of Absolute Deviation = 5.88
MSE = Mean of Error2 = 56.05
MAPE = Mean of (Abs(Error/Demand)) * 100 = 4.74%
ii)
3-Period Weighted Moving Average forecast with weights of 0.7, 0.2, and 0.1
MAD = Average of Absolute Deviation = 6.02
MSE = Mean of Error2 = 66.26
MAPE = Mean of (Abs(Error/Demand)) * 100 = 4.88%
iii)
Simple Exponential Smoothing
Exponential Smoothing (Ft+1) = αYt + (1-α) Ft
MAD = Average of Absolute Deviation = 6.25
MSE = Mean of Error2 = 64.19
MAPE = Mean of (Abs(Error/Demand)) * 100 = 5.09%
iv)
a)
If we choose MSE as performance criteria, then we should use 3-Period Moving Average as it has the lowest MSE value
b)
If we choose MAD as performance criteria, then we should use 3-Period Moving Average as it has the lowest MAD value
c)
If we choose MAPE as performance criteria, then we should use 3-Period Moving Average as it has the lowest MAPE value
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