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Littlefield Technologies

In: Business and Management

Submitted By mxg244
Words 671
Pages 3
Running head: Capacity Management

Capacity Management at Littlefield Technologies
Anteaus Rezba
Leena Alex
Marcio de Godoy
Pennsylvania State University

Initial Strategy Definition Our strategy was to keep track of each machine’s capacity and the order queue. Initially, we tried not to spend much money right away with adding new machines because we were earning interest on cash stock. However, once the initial 50 days data became available, we used forecasting analyses to predict demand and machine capacity. Our goal was to buy additional machines whenever a station reached about 80% of capacity.

Day 50 Once the initial first 50 days of data became available, we plotted the data against different forecasting methods: Moving average, weighted moving average, exponential smoothing, exponential smoothing with trend, and exponential smoothing with trend and season. Out of these five options, exponential smoothing with trend displayed the best values of MSE (2.3), MAD (1.17), and MAPE (48%). In addition, the data clearly showedprovided noted that the demand was going to follow an increasing trend for the initial 150 days at least. Following, we used regression analysis to forecast demand and machine productivity for the remaining of the simulation. As explained on in chapter 124, we used the following formula: y = a + b*x. A linear regression of the day 50 data resulted in the data shown on Table 1 (attached)below.
| |Station |
|Demand |1 |2 |
| Decision | 1M1 | 2M1 | 1M1 + 1M2 | 2M1 + 1M2 | |
| Buy |

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