Case Study of Om

Case Study of Om

  • Submitted By: jennyzww
  • Date Submitted: 05/03/2013 6:19 AM
  • Category: Technology
  • Words: 990
  • Page: 4
  • Views: 1

Case Overview:

In the simulation Game-Littlefield Technologies, our team-Traveller got 8th ranking finally. This report is the review of our decision makings during this simulation, and the reflection of what we learned from this simulation. The purpose of the game is to be the well-management team with the most cash at the end of the 7 day simulation run. Comparing with the default team “Donothing”, we gain about almost 0.9M more cash and make profit from the 1,500,000 beginning balance.

Strategy Setting:

In the capacity management part of the simulation, order demand is random and we need to do forecast the orders and build factory capacity around that. In gameplay, the demand steadily rises till the 120 days, then steadies around 70 days and then declines in three even stages. We should not overbuy production capacity during the peak, as it will leave with the excess capacity when demand dies down.

1. Demand forecast:

From the assignment presentation, we could know that the order comes as the graph as below, it will increase until about 120 days elapsed, constant average for about 70 days after this, and decreasing from then until day 203. The demand curve seems like a trapezium shape, we can see the demand grows slowly at the beginning and decrease sharply by the end, we can configure our equipment according to the trend and make the profit maximization. Since we know the trend and have the data of 35 days from the beginning, so that we think that do not need to make the forecast according to liner regression model, but just use the simple average to do the forecast.

After the rough calculation, we can afford an average demand of 16 jobs per day. And the peak of the order will not exceed 20 jobs per day. And we will add the station and adjust he order point according to the change of the utilization rate and the inventory status. We think that when utilization will max out, it is better to lose a little...

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