The sales revenue decreased from 9 million to 6 million in 12 years and also they incurred operating losses. 20 While ordering and setting the next reorder points, I kept in mind that the demand is increasing and I should have sufficient safety stock (buffer), so as not to lose revenues due to inventory shortages. Decision 1 49 Littlefield Simulation Analysis Littlefield Initial Strategy When the simulation first started we made a couple of adjustments and monitored the performance of the factory for the first few days. ROI=Final Cash-Day 50 Cash-PP&E ExpenditurePP&E Expenditure 1,915,226-97,649-280,000280,000=549% These key areas will be discussed throughout the journal to express my understanding of the experience. Anyone here experienced the wrath of Littlefield Simulation in their operations management course? Pre-production market research suggested that the average daily demand level would be somewhere between 10 orders/day and 14 orders/day. Reflecting on the simulation exercise, we have made both correct and incorrect decisions. Here are our learnings. Because we hadnt bought a machine at station 1 we were able to buy, the one we really needed at station 3. Anteaus Rezba Please refer to the appendix (Exhibit I) for detailed financials., The Elijah Heart Center needs to make changes on cost-cutting, funding options for equipment, and funding options for capital expansion. Written Assignment: Analysis of Game 2 of Littlefield Technologies Simulation Due March 14, 8:30 am in eDropbox Your group is going to be evaluated in part on your success in the game and in part on how clear, well structured and thorough your write-up is. In the final simulation, we corrected our mistakes. Because all stations were at times operating at full, we knew that all would create a bottleneck if left to operate as is. Background Aneel Gautam Current State of the System and Your Assignment On day 97, we changed Station 2s scheduling rule to priority step 2. Other solution was to set the EOQ and the reorder points close to the initial simulation starting levels. Although orders arrive randomly to LT, management expects that, on average, demand will follow the trends outlined above. Overall results and rankings. By accepting all cookies, you agree to our use of cookies to deliver and maintain our services and site, improve the quality of Reddit, personalize Reddit content and advertising, and measure the effectiveness of advertising. This weeks key learning areas have been eye opening and worthwhile. This meant an increased level of production and increased pressure on machines; therefore naturally the breakdown of machines was increasing. (Points: 30) |, The aim of this report is to provide an overview of businesses simulations through TOPSIM, a business management game that establishes a link between business management theory and business management in practice., The production capacity in my first 2 quarters was low but only because it was upcoming, The above table showing the total capacity per hour of each machine center was calculated by taking the number of machines and multiplying them by the run time per piece per minute. At s the end of this lifetime, demand will end abruptly and factory operations will be terminated. Do you feel that the Bearington plant has the right equipment and technology to do the job? performance of the factory for the first few days. However, once the initial 50 days data became available, we used forecasting analyses to predict demand and machine capacity. The best two options for the hospital to reach their goal in my opinion are, reducing the agency staff and changing the skill mix. Littlefield Technologies is an effective teaching tool that the students seem to really enjoy and the students are forced to think logically about the problems that they are facing and they learn from iterative experimentation. However, it was because we did not create a safety margin for production which came from our over estimating our carrying costs. Managing Capacity and Lead Time at Littlefield Technologies Team 9s Summary We were interested in allocating the money towards marketing as opposed to production. Nevertheless, although we ranked 4th (Exhibit 1: OVERALL TEAM STANDING), we believe we gained a deeper understanding of queuing theory and have obtained invaluable experience from this exercise. Ending Cash Balance: $1,915,226 (6th Place) We had explored few possibility of making good inventory decisions towards the day 305. 54 | station 1 machine count | 2 | Figure 1: Day 1-50 Demand and Linear Regression Model This left the factory with zero cash on hand. us: [emailprotected]. This project attempts to model this game using system dynamics approach, which allows realistic representation of the production system of Littlefield . SOMETIMES THEY TAKE A FEW MINUTES TO BE PROCESSED. 6. and I will explain as to why I choose what I did in this paper., Comparing the difference between the production volume variance of the first and second half of the year, we noticed that during the second term, it is more favorable than the first term. Leena Alex So we purchased a, machine at station 2 first. This proposal, when implemented, can save up to Rs. We know from the text that Al Beck is running two eight hour shifts so the machines are running for a minimum of 16 hours per day. In addition, we will research and tour Darigold Inc. to evaluate their operations, providing analysis and recommended changes where we deem applicable. UNSCOP recommended two solutions. Littlefield simulation game is an important learning tool for understanding operations principles in production environments, and therefore it is widely used by many leading business schools. Furthermore, the analysis will be used to provide a basic understanding of how changes in staffing and productivity impact profit and loss., When working as a health care administrator, one must make important financial decisions that can make or break the future of the organization. 1 Littlefield Labs Simulation Professor: Ioannis (Yannis) Bellos Course: MBA 638 School of Business Information Systems . With the daily average demand and SD we could control the Littlefield Labs system capacity. [pic] |BOSTON Our cash position got weaker and we then slipped to position 7 from position 2. We bought additional machines at stations with high utilization rates in an attempt to relieve those bottlenecks. This decision was taken based on a demand of 91 jobs and a utilization of station 1 of 0.83 between days 143 and, This paper will provide an analysis of 2 production scenarios. Machine stoppage data for the, One of our team members conducted a full operations analysis. On observing the 100% machine utilization at any given station for few consecutive days, we immediately added the new machines. The decision making for the machines is typically based on the utilization of machines. Littlefield Simulation Solutions and analytical decisons made. Management requires a 10% rate of return on its investments. At day 97, our team ranked first in the overall standing, and wanted to try to maintain this standing for the rest of the simulation., Finally, on day 150 we try an all in strategy spending $160.000 in 1 machine for station 1 and 2 to increase the capacity and to process jobs only on conditions of contract 3. By doing so we have a Gross profit of $1,125,189, |production increase. This work reports a laboratory experiment in which managerial performance in dynamic tasks is improved by improving the quality of decisions made in the context of a dynamic environment. Second, we controlled the inventory level with finding right QOPT (Optimal Order Quantity) and reorder point according to continuous review system method. All rights reserved. Customer Demand As soon as we noticed our lead times drop sufficiently enough for a new contract, we upgraded immediately. 0 6 comments Best Add a Comment camcamtheram 2 yr. ago 201 Littlefield Technologies (LT) has developed another DSS product. The SlideShare family just got bigger. . . Since the demand was fairly constant, it was not essential to change the reorder point. 1 Whenever we observed the delays in lead-time management and results, we used to switch back to contract-2; our safe option not to miss on the customers lead-time promise and hence not to lose the revenues. Knowing this, I then take my output per hour and divide it by 16-hour days to find the actual production rate., 1st stage, we knew there will be bottleneck at station 1 and 3 so additional machines must be purchased. Littlefield Technologies is a factory simulator that allows students to compete with each other over the web while developing operations management skills. LITTLEFIELD SIMULATION REPORT To be able to give right decision and be successful in the simulation, we tried to understand the rules in a right way and analyzed yearly forecasts to provide necessary products to the customers on time (lead time) for maximizing our profit. As a result, we continued to struggle with overproduction and avoiding stock outs, but made improvements resulting in less drastic inventory swings in the later. Our strategy was to get lead times down below .5 days and offer customers that lead time to maximize revenue. I was mainly responsible for the inventory . Once the initial first 50 days of data became available, we plotted the data against different forecasting methods: Moving average, weighted moving average, exponential smoothing, exponential smoothing with trend, and exponential smoothing with trend and season. We ended up with a total of 6 machines at station one, which allowed two orders to be simultaneously worked on with a batch of 3 x 20. Based on initial management analyses, customer demand for this new product is expected to be random, but the average demand will be level over the products 268-day lifetime. Our team finished the simulation in 3rd place, posting $2,234,639 in cash at the end of the game. Start making decisions early, i.e. At this point our orders we getting out on time with few exceptions. The first was that the area be implications of the growing role of private military companies (PMCs) for governing global politics Our decisions were somewhat limited to our EOQ models completion and our risk adversity. Steve was concerned about the potential loss of customers and suggested that Prairie Winds purchase a second pasta production machine for $40 million. 113 Customer orders processed within 1 day make $1000 Customer orders that take over 3 days make no money Between 1 and 3 days revenue is a decreasing linear function. The results and insights generated by these contributions suggest that the greatest need for future research on system dynamics and its contribution to simulation-gaming is demonstration of improvements in learning and performance. Do a proactive Inventory management during the simulation run. Moreover, we also saw that the demand spiked up.