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
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Littlefield Simulation II Based on our success in the last Littlefield Simulation‚ we tried to utilize the same strategy as last time. 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. We wanted to keep the lead time between .5 and 1 day in order to get the maximum amount of revenue per job. We utilized data from the first 50 days and put it in an Excel chart to forecast the demand for the
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Littlefield Simulation Write-up December 7‚ 2011 Operations Management 502 Team 9 Littlefield Lab We began our analysis by searching for bottlenecks that existed in the current system. It was easily identified that major issues existed in the ordering process. Without calculations‚ you could tell the reorder point was too low since the historical plots showed inventory levels at zero for two or more days at a time. The number of jobs in customer orders showed correlating spikes at the same
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Littlefield Simulation 2: Occupylittlefield With our second littlefield simulation complete‚ we have reinforced many of the concepts and lessons learned in class. We had a better understanding of the operation of the littlefield facility and how certain modifications would affect the throughput and lead time. Though we are pleased with our final results compared to the rest of the class‚ we see there is still room for improvement. We made many mistakes‚ but most importantly we have learned from
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Littlefield Simulation1 Team Synergy discussed our strategy for the Littlefield Simulation. Following is the timeline summarizing the decisions we made and the justification for those decisions. Day 50 – Bought machine for Station 1 When we first evaluated our factory‚ we noticed from days 1 to 50‚ the bottleneck was mainly Station 1. Most days‚ however‚ we were able to make our $1000 revenue. Therefore‚ our team decided that buying another machine for Station 1 would help move the bottleneck
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LittleField (1) What was your initial strategy and how/why did you change your strategy during the game?. (2) Which concepts that you learned in this course did you apply in making your decisions? Explain. (3) What did you learn from the game? General Strategy Getting into the game our strategy was to identify the bottleneck in the process and maximize its utilization. We were aiming to balance our stock so a new stock will arrive every 4 days‚ and the current stock will not run out (but will get
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Stanford University Graduate School of Business rev. August 2004 Managing Customer Responsiveness at Littlefield Technologies Background Littlefield Technologies (LT) has developed another DSS product. The new product is manufactured using the same process as the product in the assignment “Capacity Management at Littlefield Technologies” — neither the process sequence nor the process time distributions at each tool have changed. On day 0‚ the factory began operations with three stuffers‚
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MGT 9702 – SERVICE OPERATIONS I LITTLEFIELD TECHNOLOGIES – OVERVIEW Littlefield Technologies (LT) produces Digital Satellite System (DSS) receivers. These receivers are assembled from kits of electronic components procured from a single supplier. The assembly process consists of four steps carried out at 3 stations called board stuffing‚ testing and tuning. The machines at these stations cost $90‚000‚ $80‚000
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Littlefield Labs 1 Capacity Management at Littlefield Labs I. Introduction There are 3 stations in the game called sample preparing‚ testing‚ and centrifuging‚ while there are 4 steps to process the jobs. Before the game started‚ we tried to familiarize with the process of the laboratories and calculating the costs (both fixed and variable costs) based on the information on the sheet given. We did not intend to buy any machines too early‚ as we wanted to see the demand fluctuation and the
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Littlefield Technologies Game 2 Strategy – Group 28 1. CUSTOMER ORDERS AND ORDERS WAITING FOR MATERIAL: When considering the demand level and changes‚ we would configure a time series of that data using short range forecasting. Time series are important because they are often the drivers of decision models. Trend projection and regression analysis models will be used to forecast the future demand as the growth of the demand increases at a lower level‚ increases to a higher level‚ and then decreases
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