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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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 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 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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ittlefield Simulation #1: Capacity Management Team: Computronic When the simulation began‚ we quickly determined that there were three primary inputs to focus on: the forecast demand curve (job arrivals‚) machine utilization‚ and queue size prior to each station. Specifically we were looking for upward trends in job arrivals and queue sizes along with utilizations consistently hitting 100%. Upon initial analysis of the first fifty days of operations‚ the team noticed that Station 1 had reached
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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
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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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Managing Customer Responsiveness at Littlefield Labs Background Littlefield Laboratories (LL) has opened another lab. The new lab uses the same process as the lab in the assignment “Capacity Management at Littlefield Labs” — neither the process sequence nor the process time distributions at each machine have changed. On day 0‚ the lab began operations with three preparers‚ one tester‚ and one centrifuge‚ and an inventory of 160 test kits. This left the lab with $1‚000‚000 in reserves. Customer
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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. On day 50 of the simulation‚ my team‚ 1teamsf‚ decided to buy a second machine to sustain our $1‚000 revenue per day and met our quoted lead time for producing and shipping receivers. On day 97‚ we changed Station 2’s scheduling rule to priority step 2. We noticed that the bottleneck was not just at station 1‚ but at all stations‚ and that buying
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Operations Management: Process Analysis and Applications Module Changing Sources of Competitive Advantage Targeting Improvement: Operational Measures - Time T‚ Inventory I‚ Throughput rate R » Link through Little’s Law » Link to Financial Measures » Targeting improvement: CRU Computer Rentals Capacity and Flow Time Analysis » Pizza Pazza » Levers for Improvement Multi-product Capacity Management and Investment » Joint Marketing & Production Decisions » Optimal Capacity
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