# Littlefield Simulation Report Essay

1541 WordsSep 30, 20137 Pages
Executive Summary Our team operated and managed the Littlefield Technologies facility over the span of 1268 simulated days. Our team finished the simulation in 3rd place, posting \$2,234,639 in cash at the end of the game. We did intuitive analysis initially and came up the strategy at the beginning of the game. And then we applied the knowledge we learned in the class, did process analysis and modified our strategies according to the performance results dynamically. We have reinforced many of the concepts and lessons learned in class and had a better understanding of the operation of the Littlefield Technologies facility and how certain modifications would affect the throughput and lead time. The Plan - Initial Strategy Our team’s…show more content…
If we change batch size to 1*60, based on day1-50 data, the lead time is always > 0.3, and we could not use contract number 2Contract 2 to increase revenue and still have to use Ccontract number 11 Revenue will be the same as 1 which is \$1,596,000 . c. If we buy machine 3 because it's a bottleneck, without changing anything else, utilization for station 3 will become less which will cause less queue, less waiting time, less lead time, no or less penalty, more revenue. Revenue (roughly) = 12 * 1500 * (268-135) = 12*133*1500 = \$2,394,000 Machine cost = 100,000 \$2,394,000-\$100,000 = \$2,294,000 > \$1,596,000 According to our analysis, So , c) is a betterthe optimal choice whichchoice, which confirmed our aggressive machine buying strategy since Day 135. And on Day 149, and Day 170, we immediately bought machine for station 2 and 1 again when the stationsit becomes bottle neck or when lead time is more than 0.28 which caused revenue decreased to \$1,200. 3. Changing lot size : We changed lot size for 3 times. On Day 58, we changed to 2 lots/job in order to take Contract number 2 to make earn more money. On Day 64, we changed to 3 lots/job and hope the lead time would decrease. This was a big mistake we made. After this change, we noticed the queue for station #3 is very high, station #3 became bottleneck and our