We nearly bought a machine there, but this would have been a mistake. Station 2 never required another machine throughout the simulation. For the purpose of this report, we have divided the simulation into seven stages after day 50, explicating the major areas of strategically significant decisions that were made and their resulting B6016 Managing Business Operations Our team finished the simulation in 3rd place, posting $2,234,639 in cash at the end of the game. 8 August 2016. Estimate the best order quantity at peak demand. Following, we used regression analysis to forecast demand and machine productivity for the remaining of the simulation. Get started for FREE Continue. The findings of a post-game survey revealed that half or more of the . Although marketing is confident of the rough shape of demand, there Is not enough marketing data to predict the actual peak demand at this point. Estimate the minimum number of machines at each station to meet that peak demand. reorder point and reorder quantity will need to be adjusted accordingly. Management is currently quoting 7-day lead times, but management would like to charge the higher prices that customers would pay for dramatically shorter lead times. The next step was to calculate the Economic Order Point (EOP) and Re Order Point (ROP) was also calculated. Increasing the promotional budget for a product in order to increase awareness is not advisable in the short run under which of the following circumstances? Littlefield Labs makes it easy for students to see operations management in practice by engaging them in a fun and competitive online simulation of a blood testing lab. (DOC) Littlefield Simulation Write-up (1) - Academia.edu Our final inventory purchase occurred shortly after day 447. 595 0 obj<>stream Demand rate (orders / day) 0 Day 120 Day 194 Day 201. 2. capacity is costly in general, we want to utilize our station highly. Thus should have bought earlier, probably around day 52 when utilization rate hit 1. Essay on Littlefield Executive Summary Production Planning and Inventory Control CTPT 310 Littlefield Simulation Executive Report Arlene Myers: 260299905 Rubing Mo: 260367907 Brent Devenne: . In Littlefield, total operational costs are comprised of raw material costs, ordering costs and holding costs. 105 http://quick.responsive.net/lt/toronto3/entry.html 161 I'm spending too much on inventory to truly raise revenue. 65 Littlefield Simulation Report Question Title * Q1. Avoid ordering an insufficient quantity of product . Contract Pricing Do not sell or share my personal information, 1. Each customer demand unit consists of (is made from) 60 kits of material. Machine configuration: PLEASE DO NOT WAIT UNTIL THE FINAL SECONDS TO MAKE YOUR CHANGES. Open Document. Future demand for forecast was based on the information given. We tried not to spend our money right away with purchasing new machines since we are earning interest on it and we were not sure what the utilization would be with all three of the machines. Daily Demand = 1,260 Kits ROP to satisfy 99% = 5,040 Game 2 Strategy. The account includes the decisions we made, the actions we took, and their impact on production and the bottom line. Littlefield Labs makes it easy for students to see operations management in practice by engaging them in a fun and competitive online simulation of a blood testing lab. 0000007971 00000 n First of all, we purchased a second machine from Station 1; however, we could not think Station 1 would be a bottleneck process. 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For questions 1, 2, and 3 assume no parallel processing takes place. Furthermore, we thought that buying machines from Station 3 was unnecessary because of the utilization in that station. Instant access to millions of ebooks, audiobooks, magazines, podcasts and more. Revenue For most of the time, step 4 was selected as the step to process first. Thus, at the beginning, we did not take any action till Day 62. DAY 1 (8 OCTOBER 3013) Littlefield Technologies Part 1 - 664 Words | Bartleby The initial goal of the goal was to correlate the Re Order Point with the Customer Order Queue. This quantity minimizes the holding and ordering costs. We took the per day sale data that we had and calculated a linear regression. We nearly bought a machine there, but this would have been a mistake. We thought because of our new capacity that we would be able to accommodate this batch size and reduce our lead-time. As we will see later, this was a slight mistake since the interest rate did have a profound impact on our earnings compared to other groups. Thus our inventory would often increase to a point between our two calculated optimal purchase quantities. 0000001482 00000 n Click on the links below for more information: A mini site providing more details and a demo of Littlefield Technologies, How to order trial accounts, instructor packets, and course accounts, The students really enjoyed the simulation. To . However, we realize that we are not making money quick enough so we change our station 2 priority to 4 and use the money we generate to purchase additional machine at station 1. Future Students Current Students Employees Parents and Family Alumni. until day 240. When do we retire a machine as it 54 | station 1 machine count | 2 | 0 The model requires to, things, the order quantity (RO) and reorder point (ROP). Start New Search | Return to SPE Home; Toggle navigation; Login; powered by i These reports enable factory managers to quickly assess performance and make Littlefield strategy decisions. After all of our other purchases, utilization capacity and queuing at station 2 were still very manageable. 0000004706 00000 n Littlefield Simulation II Day 1-50 Robert Mackintosh Trey Kelley Andrew Spinnler Kent Johansen 98 | Buy Machine 1 | The utilization of Machine 1 on day 88 to day 90 was around 1. In addition, because the factory is essentially bootstrapping itself financially, management is worried about the possibility of bankruptcy. The cost of not receiving inventory in time with a promised lead-time of 0.5 days was way too high. FAQs for Littlefield Simulation Game: Please read the game description carefully. We expect that there will be 4 different stages of demand that will occur throughout thesimulation, which are: Stage 1: slight increasing in demand from day 1 to day 60 Stage 2: highly increase in demand from day 60 to day 240 Stage 3: demand peaks from day 240 to day 300 Stage 3: sharp decrease in demand from day 300 to day 360. Based on our success in the last Littlefield Simulation, we tried to utilize the same strategy as last time. Our team operated and managed the Littlefield Technologies facility over the span of 1268 simulated days. Essentially, what we're trying to do with the forecast is: 1. Using the EOQ model you can determine the optimal order quantity (Q*). required for the different contract levels including whether it is financially viable to increase 265 Before the simulation started, our team created a trend forecast, using the first 50 days of data, showing us that the bottleneck station was at Station 1. Anise Tan Qing Ye By getting the bottleneck rate we are able to predict which of the . Please discuss whether this is the best strategy given the specific market environment. Question 1 Demand Forecasting We were told that demand would be linearly increasing for the first 90-110 days, constant till day 180 and then fall off after that. the forecast demand curve (job arrivals) machine utilization and queue . Littlefield was developed with Sunil Kumar and Samuel Wood while they were on the faculty of Stanfords Graduate School of Business. Our team operated and managed the Littlefield Technologies facility over the span of 1268 simulated days. 0000002541 00000 n You are in: North America I know the equations but could use help finding daily demand and figuring it out. The. Plan We took the sales per day data that we had and calculated a liner regression. 10% minus taxes Forecast of demand: Either enter your demand forecast for the weeks requested below, or use Excel to create a . search.spe.org %PDF-1.3 % 1. Looks like youve clipped this slide to already. Therefore, the optimal order quantity (Q*) is 1721 units. Upon further analysis, we determined the average demand to date to have been 12. Demand forecasting is a tool that helps customers in the manufacturing industry create forecasting processes. We found the inventory process rate at stations 1 and 3 to be very similar. 1 Our goals were to minimize lead time by reducing the amount of jobs in queue and ensuring that we had enough machines at each station to handle the capacity. The Economic Order Quantity (EOQ) minimizes the inventory holding costs and ordering costs. Course Hero is not sponsored or endorsed by any college or university. We used demand forecast to plan purchase of our machinery and inventory levels. 20000 Plugging in the numbers $2500*.00027=.675, we see that the daily holding cost per unit (H) is $0.675. Improving Undergraduate Student Performance on the Littlefield Simulation The first time our revenues dropped at all, we found that the capacity utilization at station 2 was much higher than at any of the other stations. We also need to calculate the holding cost (H). Forecasting - Overview, Methods and Features, Steps
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