Littlefield Technology Game Capacity Essay

The naughty was held over a week and enabled us to increase our arrest of inventory management at the doing stage in the issue kitchen stove. In this game, the objective was to accomplish production and delivery of the production at bottom 3 days of lead time. Over the course of the game, we were to monitor the production numbers and make adjustments through the number of weapons which we owned. works affected the revenues through the procures and the stopping point was to obtain as much revenue as possible. Through the game, we learnt how to discerp our production numbers and plot strategies to tackle the have that was constantly changing. schemaOur strategy was to obtain a stable role rate throughout all railcars to prevent incurring all late penalty. For example at Day 50, earlier the game started, we observed that machine 1 was caterpillar track at 100% usance for a few days before, and we predicted a bottleneck placement would occur here. indeed we decided to purchase an additive machine immediately as the game started so as to forgo continuous processing of lots to meet the demand and prevent losses in revenue. After purchasing additional machine 1, we lived observing the utilization of the machine. We were careful not to buy additional machines unnecessarily so that we can earn more(prenominal) revenue from the delight. On day 88, machine 1 hit 100% utilization for 4 consecutive days. However, the second-rate revenue earned was still $1000 despite the high utilization.Therefore we decided not to purchase additional machines at carry 1. This turn up to our favour as the revenue earned did not cast out during this plosive speech sound of time even though station 1 utilization continue to be close to 1. Furthermore, we move to earn a higher interest than other teams who bought additional machines. Due to this plan, we were amongst the top few teams at this termination of time. At day 120, a situation similar to day 88 beg an to occur machine 1 hit 100% utilization forever for 6 days and continue to hit close to 100% for the next few days. We had thought that we could tide through it like before without the wish of an additional machine. However, this time round, a bottleneck formed at station 1 and the revenue started to drop quite severely. Therefore, we decided that an additional machine is needed at station 1 to prevent further drop in the revenue. However, the purchase of an additional machine did not salvageour situation as the queue size at station 1 was as well large.During this period, a lot of income was lost due to our production not cosmos able to meet the 3 days of lead time. Our revenue but stabilized on day 130 for 2 days before dipping a come across. This time, the bottleneck transferred to station 3 and the queue has risen drastically to approximately 600 jobs. Therefore, we made the decision to purchase another machine for station 3. With this, our revenue finally stabilised at day 139. In the following days, we continued the strategy of monitoring the revenue, as well as the stations utilization and queue size, before deciding whether to purchase additional machines. Following this strategy, we acquired a total of 4 work 1s, 2 Machine 2s and 2 Machine 3s. As the demand fell towards the end of the game, we decided to sell clear up machines at the under-utilized stations so that we could increase our revenue from the sales of the machines, as well as gain more interest, and increase our ranking before the game ends.Therefore, at the end, we were left with 3 Machine 1s, 1 Machine 2 and 2 Machine 3s. In the case of station 2, which kill dance steps 2 and 4 of the production, we were able to toggle between trio policies giving priority to First In First Out (FIFO), step 2 or step 4. In the early stages of the game, the utilization at station 2 throwed at a relatively natural rubber level. However, at about day 120, the average demand began to increase and the utilization began to hit 100%. It remained at this range until we made the decision to purchase an additional machine for the station at day 150. As the surgical operation of station 2 affects the jobs arriving at station 3, the delays in production snowballed and this drastically affected our revenue.ConclusionIn hindsight, it is unfortunate that we were not able to maintain our advantage as the leading few teams. We suffered a major about-face during the day 120 period due to unexpected demand spikes and paltry decision making. However, we did manage to salvage our situation in the end and obtained a respectable rank of 7th place. We have learnt that we cannot assume the best of any situation and that we have to be prepared for sudden influx of demand and also that there is no one size fits all policy. The game simulates a real assembly scenario. While the strategy helped us gain revenue, the scenario does not comply with certain real life supply chain conditions such a s taxes. All fixed overhead which we have no control, such as salaries,rent, utilities, etc. are ignored. These factors will introduce more complexities into making decisions.