...Background In early January 2006, Littlefield Technologies (LT) opened its first and only factory to produce its newly developed Digital Satellite System (DSS) receivers. Littlefield Technologies mainly sells to retailers and small manufacturers using the DSS’s in more complex products. Littlefield Technologies charges a premium and competes by promising to ship a receiver within 24 hours of receiving the order, or the customer will receive a rebate based on the delay. The product lifetime of many high-tech electronic products is short, and the DSS receiver is no exception. LT managers have decided that, after 268 days of operation, the plant will cease producing the DSS receiver, retool the factory, and sell any remaining inventories. As this is a short life-cycle product, managers expect that demand during the 268 day period will grow as customers discover the product, eventually level out, and then decline. In the initial months, demand is expected to grow at a roughly linear rate. Demand is then expected to stabilize. Eventually, demand should begin to decline at a roughly linear rate. Although orders arrive randomly to LT, management expects that, on average, demand will follow the trends outlined above. Management’s main concern is managing the capacity of the factory in response to the complex demand pattern. Delays resulting from insufficient capacity undermine LT’s promised lead times and ultimately force LT to turn away orders. In particular, if an order’s...
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...Littlefield Technologies Assignment 5 PM on February 22 . Starting at 5 PM on Wednesday, February 27, the simulation will begin The game will end at 9 PM on Sunday, March 3. Accessing your factory http://quick.responsive.net/lt/toronto3/entry.html Littlefield Technologies’ Operations board stuffing testing tuning Operations Policies at Littlefield Purchasing Supplies Processing in Batches Contract Pricing Borrowing from the Bank Cash Balance The winning team is the team with the most cash at the end of the game (cash on hand less debt). Current State of the System and Your Assignment At the end of day 350, the factory will shut down and your final cash position will be determined. Starting at 5 PM on Wednesday, February 27, the simulation will begin The game will end at 9 PM on Sunday, March 3. PLEASE DO NOT WAIT UNTIL THE FINAL SECONDS TO MAKE YOUR CHANGES. SOMETIMES THEY TAKE A FEW MINUTES TO BE PROCESSED. 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. The write-up only covers the second round, played from February 27 through March 3. It should not discuss the first round. Your write-up should address the following points: • A brief description of what actions you chose and when. Not a full list of every action, but the major...
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...getting second place on the first Littlefield simulation game we knew what we needed to do to win the second simulation game. We were very eager to outperform our competition and we almost did so, but ended up in second place again with a cash balance of $2,660,393. The second Littlefield simulation game focused on lead time and inventory management in an environment with a changing demand (“but the long-run average demand will not change over the product’s 268-day lifetime”). Therefore our strategy to win this game was controlling the Littlefield Lab’s system capacity and the inventory level with choosing a right contract as well as keeping the cash daily as much as possible. In other words, we first needed to find daily average demand and match it to the Littlefield Lab’s system capacity. Second, we controlled the inventory level with finding right QOPT (Optimal Order Quantity) and reorder point according to continuous review system method. Lastly we chose the right contract among our 3 options to maximize the profits according to daily average job lead-time. When first approaching this game we met to strategize, forecast, make a meeting schedule, and divide the work. At our first meeting we analyzed the first given 50 days so that we could get the daily average demand and SD (Standard Deviation). First, 50 days of daily average demand was 15.50 and SD was 4.12. With the daily average demand and SD we could control the Littlefield Lab’s system capacity. Since...
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...[pic] |BOSTON COLLEGE |CARROLL SCHOOL OF MANAGEMENT OPERATIONS & STRATEGIC MANAGEMENT | | Managing Customer Responsiveness at Littlefield Technologies – Spring 2007( Background It is now nine months later, and Littlefield Technologies has developed another DSS product. This product also is expected to have a 268-day lifetime. Littlefield once again has contracted with your operations management consulting team to manage their operations for this new product. Management Strategy Littlefield’s management would like to be able to charge the premium prices that customers would be willing to pay for dramatically shorter lead times. However, management has found that historic lead times[1] during the first 50 days of production often extend into several days, and so they have been unwilling to quote the shorter lead times to customers. They want your team to look into why this is occurring, and hopefully remedy the situation. Customer Demand 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 product’s 268-day lifetime. Pre-production market research suggested that the average daily demand level would be somewhere between 10 orders/day and 14 orders/day. Closer to Day 50, shop floor space constraints are limiting the number of jobs being accepted into the factory. Management is concerned about this outcome. At the end of this product’s lifetime, demand will...
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...Lead Time Management at Littlefield Labs Background Littlefield Laboratories has opened a new blood testing lab. This laboratory uses the same process as the lab encountered in your prior assignment, Capacity Management at Littlefield Labs—neither the process sequence nor the process time distributions have changed. The lab began operations with a raw materials inventory of 160 kits and $1,000,000 cash. Customer demand continues to be random, but the expected daily demand will not change during the lab’s life span. Expert advisors know that demand will end abruptly on Day 268 and the lab will no longer be necessary. Any remaining machinery or inventory will be useless after Day 268, and thus have no residual value. Management would like to increase revenue and decrease costs. They believe a more responsive laboratory will increase revenue and they understand well-balanced inventory policies ought to minimize costs. Operations Policies at Littlefield In appreciation of your prior recommendations and contributions, Littlefield has once again retained your services on their 50th day of operations. This time, they would like your help with further lead time improvements and optimizing their inventory policy. Management has used process time estimates from your first report to calculate a stable capacity configuration. They have purchased the recommended machinery, but are not entirely pleased with the lead time performance. Management trusts you will be able to effectively...
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...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. The LT factory began production by investing most of its cash into capacity and inventory. Specifically, on day 0, the factory began operations with three stuffers, two testers, and one tuner, and a raw materials inventory of 9600 kits. This left the factory with zero cash on hand. Customer demand continues to be random, but the long-run average demand will not change over the product’ 486-day lifetime. At s the end of this lifetime, demand will end abruptly and factory operations will be terminated. At this point, all capacity and remaining inventory will be useless, and thus have no value. 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. In addition, because the factory is essentially bootstrapping itself financially, management is worried about the possibility of bankruptcy. To minimize this threat, management policy dictates that new equipment cannot be purchased if the remaining cash balance would be insufficient to purchase at least one order quantity’ worth of raw materials. s Operations Policies at Littlefield LT uses...
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...investment in the machine. Having more machines seemed like a win-win situation since it does not increase our expenses of running the business, yet decreases our risk of having lead times of over a day. The only expense we thought of was interest expense, which was only 10% per year. Therefore, we took aproactive approach to buying machines and purchased a machine whenever utilization rates rose dangerously high or caused long queues. 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. Machine configuration: Our final machine configuration (which was set on Day 67) was 3 machine 1's, 2 machine 2's, and2 machine 3's. This lasted us through the whole simulation with only a slight dip in revenue during maximum demand. In terms of choosing a priority for machine 2, we decided to switch to priority to step 2 since machine 2's utilization was consistently higher than machine 3's. We wanted machine 3 to never be idle and thus, kept the priority at 2. However, the difference in choosing between the priorities seemed minimal and is probably only important during times of high demand. Forecasting: We set up a spreadsheet to forecast demand...
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...ev ev Littlefield Simulation Report: Team A Ending Cash Balance: $1,915,226 (6th Place) Return On Investment: 549% ROI=Final Cash-Day 50 Cash-PP&E ExpenditurePP&E Expenditure→ 1,915,226-97,649-280,000280,000=549% Analysis of the First 50 Days The Littlefield Technologies management group hired Team A consulting firm to help analyze and improve the operational efficiency of their Digital Satellite Systems receivers manufacturing facility. Upon the preliminary meeting with Littlefield management, Team A were presented with all pertinent data from the first 50 days of operations within the facility in order for the firm to analyze and develop an operational strategy to increase Littlefield’s throughput and ultimately profits. Figure 1: Day 1-50 Demand and Linear Regression Model Figure 1: Day 1-50 Demand and Linear Regression Model With little time to waste, Team A began by analyzing demand over the first 50 days of operations in order to create a linear regression model to predict demand into the future in order to make critical operational decisions; refer to Figure 1. In Littlefield, total operational costs are comprised of raw material costs, ordering costs and holding costs. Raw material costs are fixed, therefore the only way to improve the facility’s financial performance without changing contracts is to reduce ordering and holding costs. As such, the first decision to be made involved inventory management and raw material ordering. Inventory management...
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...June 9, 2013 Section 2, Team 9 Managing Capacity and Lead Time at Littlefield Technologies – Team 9’s Summary The purpose of this simulation was to effectively manage a job shop that assembles digital satellite system receivers. The objective was to maximize cash at the end of the product life-cycle (270 days) by optimizing the process design. REVENUE 25000 20000 15000 10000 5000 1 9 17 25 33 41 49 57 65 73 81 89 97 105 113 121 129 137 145 153 161 169 177 185 193 201 209 217 225 233 241 249 257 265 Total Revenue Demand DAYS 0 Figure 1 : Revenue and demand DEMAND 25 20 15 10 5 0 As shown by the figure above, total revenues generally followed the same trend as demand. The few sections of negative correlation formed the basis for our critical learning points. Although the process took a while to completely understand during the initial months of the simulation, the team managed to adjust, learn quickly and finish in 7th place with a cash balance of $1,501,794. 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 effects...
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...first increased our inventory reorder point to 10,800 units and changed the order quantity amount to 1800 units. In order to process this increase in units, we bought 2 machines for station 1, 3 machines for station 2, and 2 machine for station 3. Seeing that the machines could process a lot more inventory faster than we expected, we decided to change our reorder points and order quantities, to 6000 units and 24,000 units, respectively. After letting our system adjust to the changes, we moved to contract 2 when the lead time was decreased to about 1 day. From there we let the simulation run for another six days before lead times went down to less than 1, at which time we switched to contract 3. We made no further changes after switching to contract 3. Part 1: Reasoning for Decisions Our decisions were somewhat limited to our EOQ model’s completion and our risk adversity. In the last simulation we relied much more heavily on our EOQ model and planned out purchases of machinery with the raise in demand. However, it was because we did not create a safety margin for production which came from our over estimating our carrying costs. We knew that the initial status quo was limited by the inventory quantity. But we did not know if it was the reason for the full utilization of the machinery. Thus we decided to change the most pressing variable, inventory, and see where it went from there. But we knew that this time we needed to act faster than before to acquire new machinery....
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...Thundercats Team Contract November 4th, 2014 Mission The mission of our team is to complete all aspects of the team assignment on time and to the full requirements set forth by Professor McNickle. Project We will work to the best of our abilities on the Littlefield simulation and will work as a team to make agreed upon manufacturing changes as often as is deemed needed. In addition, we will research and tour Darigold Inc. to evaluate their operations, providing analysis and recommended changes where we deem applicable. Our goal is to function as a reciprocal interdependent team, using each members’ varied skills and time to complete tasks both well and on time. To ensure we are focused and accomplish these set goals, the following guidelines...
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...B6016 Managing Business Operations Report on Littlefield Technologies Simulation Exercise By Group 4: Anise Tan Qing Ye Aneel Gautam Chu Kar Hwa, Leonard Tan Kok Wei Ranking Reflecting on the simulation exercise, we have made both correct and incorrect decisions. 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. Rank | Team | Cash Balance ($) | 1 | bigmoney1 | 1,346,320 | 2 | techwizard | 1,312,368 | 3 | makebigmoney | 1,141,686 | 4 | beaters123 | 895,405 | 5 | donothing | 588,054 | 6 | mas001 | 472,296 | Exhibit 1 : OVERALL TEAM STANDING Decisions Made A summary of the rationale behind the key decisions made would perhaps best explain the results we achieved. . Decision 1 Day | Parameter | Value | 54 | station 1 machine count | 2 | When the exercise started, we decided that when the lead time hit 1 day, we would buy one station 1 machine based on our analysis that station 1 takes the longest time which is 0.221 hrs simulation time per batch. (Exhibit 2: Average time per batch of each station). As day 7 and day 8 have 0 job arrivals, we used day 1-6 figures to calculate the average time for each station to process 1 batch of job arrivals. Base on the average time taken to process 1 batch of job arrivals, we were able to figure out how many...
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...Running head: Capacity Management Capacity Management at Littlefield Technologies Anteaus Rezba Leena Alex Marcio de Godoy Pennsylvania State University Initial Strategy Definition Our strategy was to keep track of each machine’s capacity and the order queue. Initially, we tried not to spend much money right away with adding new machines because we were earning interest on cash stock. However, once the initial 50 days data became available, we used forecasting analyses to predict demand and machine capacity. Our goal was to buy additional machines whenever a station reached about 80% of capacity. Day 50 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. Out of these five options, exponential smoothing with trend displayed the best values of MSE (2.3), MAD (1.17), and MAPE (48%). In addition, the data clearly showedprovided noted that the demand was going to follow an increasing trend for the initial 150 days at least. Following, we used regression analysis to forecast demand and machine productivity for the remaining of the simulation. As explained on in chapter 124, we used the following formula: y = a + b*x. A linear regression of the day 50 data resulted in the data shown on Table 1 (attached)below. | |Station ...
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...The Israeli-Palestinian conflict has been one of the most important issues that the United Nations has focused on since its founding in 1945. It has been the central topic for many resolutions, special committees, and peacekeeping efforts over the last sixty years. The United Nations has served as a platform for discussion about this conflict and has been used as a mediator between the opposing groups as a peaceful resolution to the issues is sought. Its main interest is in creating a peaceful end to this conflict and ensuring that both sides are just in their actions. At the time that the United Nations was founded, Great Britain administered the area of Palestine as a result of a mandate that had been assigned to them by the League of Nations. The British supported the establishment of a Jewish state in the area and Jewish immigration was greatly increasing especially following the Holocaust during World War II. This was met by opposition from the Arab population in Palestine and, as violence between the groups increased, the British were forced to turn the region over to the United Nations. On 28 April 1947 a special session of the UN General Assembly established the Special Committee on Palestine (UNSCOP), which had the task of investigating all of the questions surrounding the problems in Palestine and to recommend solutions to be considered by the General Assembly later that year. UNSCOP recommended two solutions. The first was that the area be divided...
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...implications of the growing role of private military companies (PMCs) for governing global politics Introduction The focus of the investigation, the findings of which are presented in this essay, was on the implications for the governance of global politics of the growing role of private military companies (PMCs). PMCs are different from traditional military contractors, which more often than not are referred to as defense contractors. Traditional military (or defense) contractors manufacture the weapons of war, provide the supplies that are required by armed forces, or perform other services that do not directly involve their personnel in combatant roles. Private military companies, in contrast to traditional military contractors provide both direct military services and security services. PMC personnel are directly involved in combatant roles when the contract provides for the delivery of military capacities. PMC personnel may be directly involved in combatant roles when the contract provides for the delivery of security services. PMC personnel providing security services must be prepared to engage in combatant roles; however, much of their duties will be as guards to prevent breeches of security. In the investigation, the results of which are presented in this study, the implications of the growing role of PMCs on the governance of global politics considers the effects of PMCs in both their military roles and their security roles. While the direct combatant roles...
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