Littlefield Executive Summary
Production Planning and Inventory Control
CTPT 310
Littlefield Simulation Executive Report
Arlene Myers: 260299905
Rubing Mo: 260367907
Brent Devenne: 260339080
Miyaoka Scenario, Re: Littlefield Technology Simulation Game: Inventory Management
Executive Summary
At the onset of the game, we determined there were a few key things that had to be addressed to succeed. The first was to avoid stock outs which had already occurred in the first 50 days. We quickly moved to avoid stock outs by raising the order point. We did this without formal calculations at first to ensure we did not suffer anymore stock outs while we did the analyses. Upon further analysis, we determined the average demand to date to have been 12.3 orders per day. We forecast demand to stay relatively stable throughout the game based on the information provided. The standard deviation for the period was 3.64 and the safety factor we decided to use was 3.0 (98.86% certainty). Based on the consistent lead time of 4 days, we needed ≈49 kits plus safety stock of 2 x 3.64 x 3 ≈22 which gave us our order point of 71 kits.
Immediately after determining this, we moved to the EOQ:
EOQ=2* 3216*1000.1* 600
This equation gave us our final order quantity of 327, although based on slight demand fluctuations we had been at 321 prior to that.
Our next move was to determine what machines need to be purchased and how many. Our strategy was to get lead times down below .5 days and offer customers that lead time to maximize revenue. The difference between remaining at $750/order vs. $1250/order could have been as high as 1.3 million dollars over the life of the game (218 days) therefore the cost of new machines was small compared to the benefit and the overall revenue potential made it imperative to get to the lowest lead times possible. Because all stations were at times operating at full, we knew that all would create a bottleneck if left to operate as is. We could also see based on the
CTPT 310
Littlefield Simulation Executive Report
Arlene Myers: 260299905
Rubing Mo: 260367907
Brent Devenne: 260339080
Miyaoka Scenario, Re: Littlefield Technology Simulation Game: Inventory Management
Executive Summary
At the onset of the game, we determined there were a few key things that had to be addressed to succeed. The first was to avoid stock outs which had already occurred in the first 50 days. We quickly moved to avoid stock outs by raising the order point. We did this without formal calculations at first to ensure we did not suffer anymore stock outs while we did the analyses. Upon further analysis, we determined the average demand to date to have been 12.3 orders per day. We forecast demand to stay relatively stable throughout the game based on the information provided. The standard deviation for the period was 3.64 and the safety factor we decided to use was 3.0 (98.86% certainty). Based on the consistent lead time of 4 days, we needed ≈49 kits plus safety stock of 2 x 3.64 x 3 ≈22 which gave us our order point of 71 kits.
Immediately after determining this, we moved to the EOQ:
EOQ=2* 3216*1000.1* 600
This equation gave us our final order quantity of 327, although based on slight demand fluctuations we had been at 321 prior to that.
Our next move was to determine what machines need to be purchased and how many. Our strategy was to get lead times down below .5 days and offer customers that lead time to maximize revenue. The difference between remaining at $750/order vs. $1250/order could have been as high as 1.3 million dollars over the life of the game (218 days) therefore the cost of new machines was small compared to the benefit and the overall revenue potential made it imperative to get to the lowest lead times possible. Because all stations were at times operating at full, we knew that all would create a bottleneck if left to operate as is. We could also see based on the