3. The cost of not receiving inventory in time with a promised lead-time of 0.5 days was way too high. As the demand for orders increases, the reorder We will be using variability to Raw material costs are fixed, therefore the only way to improve the facilitys financial performance without changing contracts is to reduce ordering and holding costs. 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. Summary of actions 593 17 V8. 0000002816 00000 n ](?='::-SZx$sFGOZ12HQjjmh sT!\,j\MWmLM).k" ,qh,6|g#k#>*88Z$B \'POXbOI!PblgV3Bq?1gxfZ)5?Ws}G~2JMk c:a:MSth. Based on Economy. We took the per day sale data that we had and calculated a linear regression. S=$1000 Tap here to review the details. It can increase profitability and customer satisfaction and lead to efficiency gains. Simulation: Simulation forecasting methods imitate the consumer choices that give rise to demand to arrive at a forecast. the components on PC boards and soldering them at the board stuffing station . El juny de 2017, el mateix grup va decidir crear un web deDoctor Who amb el mateix objectiu. After all of our other purchases, utilization capacity and queuing at station 2 were still very manageable. The product lifetime of many high-tech electronic products is short, and the DSS receiver is no exception. This is because we had more machines at station 1 than at station 3 for most of the simulation. In two days, we spend a lot of money on kits so we realize we only needed two machines at station 2 and 3. We analyzed in Excel and created a dashboard that illustrates different data. The team ascertained our job completion and our Lead Time. The first time our revenues dropped at all, we found that the capacity utilization at station 2 was much higher than at any of the other stations. D~5Z>;N!h6v$w 129 Using the EOQ model you can determine the optimal order quantity (Q*). We did intuitive analysis initially and came up the strategy at the beginning of the game. We've updated our privacy policy. Change location. Based on our success in the last Littlefield Simulation, we tried to utilize the same strategy as last time. 81 Station Utilization: Anteaus Rezba Our team finished the simulation in 3rd place, posting $2,234,639 in cash at the end of the game. Which elements of the learning process proved most challenging? 1541 Words. Leena Alex The managing of our factory at Littlefield Technologies thought us Production and Operations Management techniques outside the classroom. littlefield simulation demand forecastingmort de luna plus belle la vie chasse au trsor gratuite 8 ans; The United Methodist Children's Home (UMCH) is a non-profit faith-based organization dedicated to serving vulnerable children and families in crisis across Alabama and Northwest Florida. Which station has a bottleneck? In the LittleField Game 2, our team had to plan how to manage the capacity, scheduling, purchasing, and contract quotations to maximize the cash generated by the lab over its lifetime. We used demand forecast to plan purchase of our machinery and inventory levels. Explanations. 35.2k views . 0 This proved to be the most beneficial contract as long as we made sure that we had the machines necessary to accommodate the increasing demand through day 150. 5000 At day 50. Thus our inventory would often increase to a point between our two calculated optimal purchase quantities. . Why? This method relies on the future purchase plans of consumers and their intentions to anticipate demand. 177 tuning Thus should have bought earlier, probably around day 52 when utilization rate hit 1. Led by a push from Saudi Arabia and Russia, OPEC will lower its production ceiling by 2 million B/D from its August quota. One evaluation is that while we were unable to predict the future demand trends from day . PLEASE DO NOT WAIT UNTIL THE FINAL SECONDS TO MAKE YOUR CHANGES. On day 50 of the simulation, my team, 1teamsf, decided to buy a second machine to sustain our $1,000 revenue per day and met our quoted lead time for producing and shipping receivers. S: Ordering cost per order ($), and .o. 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. Calculate the inventory holding cost, in dollars per unit per year. pdf, EMT Basic Final Exam Study Guide - Google Docs, Test Bank Chapter 01 An Overview of Marketing, NHA CCMA Practice Test Questions and Answers, Sample solutions Solution Notebook 1 CSE6040, CHEM111G - Lab Report for Density Experiment (Experiment 1), Leadership class , week 3 executive summary, I am doing my essay on the Ted Talk titaled How One Photo Captured a Humanitie Crisis https, School-Plan - School Plan of San Juan Integrated School, SEC-502-RS-Dispositions Self-Assessment Survey T3 (1), Techniques DE Separation ET Analyse EN Biochimi 1, Operations and Supply Management (SCM 502). Our goal was to buy additional machines whenever a station reached about 80% of capacity. We also reorder point (kits) and reorder quantity (kits), giving us a value of 49 and 150. Plan This condition results in the link between heritage and tourism to be established as juxtaposed process, which gives rise to the need to broaden the concept of heritage and how it can be used through tourism to . After viewing the queues and the capacity utilization at each station and finding all measures to be relatively low, we decided that we could easily move to contract 3 immediately. 10% minus taxes Forecast of demand: Either enter your demand forecast for the weeks requested below, or use Excel to create a . We tried to get our bottleneck rate before the simulation while we only had limited information. This taught us to monitor the performance of the machines at the times of very high order quantities when considering machine purchases. Therefore, the optimal order quantity (Q*) is 1721 units. The winning team is the team with the most cash at the end of the game (cash on hand less debt). We took the sales per day data that we had and calculated a liner regression. Free access to premium services like Tuneln, Mubi and more. From the instruction Responsive Learning Technologies 2010. July 27, 2021. %PDF-1.3 % Yellow and gray lines represent maximum and minimum variability based on two standard deviations (95%). DAYS Posted by 2 years ago. Next we calculated what Customer Responsiveness Simulation Write-Up specifically for you for only $16.05 $11/page. From that day to day 300, the demand will stay at its peak and then start dropping 145 Round 1: 1st Step On the first day we bought a machine at station 1 because we felt that the utilisation rates were too high. Subjects. We did calculate reorder points throughout the process, but instead of calculating the reorder point as average daily demand multiplied by the 4 days required for shipment we used average daily demand multiplied by 5 days to make sure we always had enough inventory to accommodate orders. 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. We than, estimated that demand would continue to increase to day, 105. Specifically, on day 0, the factory began operations with three stuffers, two testers, and one tuner, and a raw materials inventory of 9600 kits. Going into this game our strategy was to keep track of the utilization for each machine and the customer order queue. 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. Q1: Do we have to forecast demand for the next 168 days given the past 50 days of history? and then took the appropriate steps for the next real day. ROI=Final Cash-Day 50 Cash-PP&E ExpenditurePP&E Expenditure 1,915,226-97,649-280,000280,000=549% March 19, 2021 Unfortunately not, but my only advice is that if you don't know what you're doing, do as little as possible so at least you will stay relatively in the middle Business Law: Text and Cases (Kenneth W. Clarkson; Roger LeRoy Miller; Frank B. models. Hewlett packard company Hewlett Packard Company Deskjet Printer Supply Chain, Toyota Motor Manufacturing Inc - Case Study, Silvio Napoli at Schindler India-HBS Case Study, Kristins Cookie Company Production process and analysis case study, Donner Case, Operation Management, HBR case, GE case study two decade transformation Jack Welch's Leadership, GE's Two-Decade Transformation: Jack Welch's Leadership. Since the Littlefield Lab simulation game is a team game on the internet, played for the first time at an English-speaking university in Vietnam, it is . This method verified the earlier calculation by coming out very close at 22,600 units. Please create a graph for each of these, and 3 different forecasting techniques. Thus, we did not know which machine is suitable for us; therefore, we waited 95 days to buy a new machine. cost for each test kit in Simulation 1 &2. At this point we knew that demand average would stabilize and if we could make sure our revenue stayed close to the contract mark we wouldnt need any more machines. We did not have any analysis or strategy at this point. LITTLEFIELD TECHNOLOGIES It should not discuss the first round. Operations at Littlefield Labs Littlefield Labs uses one kit per blood sample and disposes of the kit after the processing of the sample is completed After matching the sample to a kit, LL then processes the sample on a four step process on three machines as shown in Figure 2. 33 Identify several of the more common forecasting methods Measure and assess the errors that exist in all forecasts fManagerial Issues Clearing Backlog Orders = 4.367 + 0.397 Putting X = 60, we forecasted the stable demand to be around 35 orders per day. 0000002588 00000 n Littlefield Simulation Project Analysis. This is a tour to understand the concepts of LittleField simulation game. ev 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. Our strategy throughout the stimulation was to balance our work station and reduce the bottleneck. The few sections of negative correlation formed the basis for our critical learning points. %%EOF Initially, we tried not to spend much money right away with adding new machines because we were earning interest on cash stock. Starting at 5 PM on Wednesday, February 27, the simulation will begin The game will end at 9 PM on Sunday, March 3. : It offers the core functionality of a demand forecasting solution and is designed so that it can easily be extended. 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? So the reorder quantity was very less because the lead time was 4 days and with average demand of 13 the inventory in hand would be finished in 2 days which means no production for the next 2 days until . Our final inventory purchase occurred shortly after day 447. For information on the HEOA, please go to http://ed.gov/policy/highered/leg/hea08/index.html. 1. 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. 0000001740 00000 n We came very close to stocking out several times, but never actually suffered the losses associated with not being able to fill orders. 2455 Teller Road Students also viewed HW 3 2018 S solutions - Homework assignment Now customize the name of a clipboard to store your clips. To Regression Analysis: The regression analysis method for demand forecasting measures the relationship between two variables. This new feature enables different reading modes for our document viewer. This will give you a more well-rounded picture of your future sales View the full answer Tags. 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 over the course of the project. Management's main concern is managing the capacity of the lab in response to the complex . 5% c. 10% d. 10% minus . Leverage data from your ERP to access analytics and quickly respond to supply chain changes. 2. 193 What are the key insights you have gained from your work with the simulation; 2. In particular, we have reversed the previous 50 days of tasks accepted to forecast demand over the next 2- 3 months in the 95% confidence interval. Each line is served by one specialized customer service, All questions are based on the Barilla case which can be found here. We needed to have sufficient capacity to maintain lead times of less than a day and at most, 1 day and 9 hours. We calculate the reorder point Our team finished the simulation in 3rd place, posting $2,234,639 in cash at the end of the game. There is a total of three methods of demand forecasting based on the economy: Macro-level Forecasting: It generally deals with the economic environment which is related to the economy as calculated by the Index of Industrial . In addition, the data clearly showedprovided noted that the demand was going to follow an increasing trend for the initial 150 days at least. and Write a strategy to communicate your brand story through: Each hour of real time represents 1 day in the simulation. Littlefield Technologies mainly sells to retailers and small manufacturers using the DSS's in more complex products. 2013 0000003942 00000 n Tan Kok Wei It was easily identified that major issues existed in the ordering process. Strategies for the Little field Simulation Game 1 Even with random orders here and there, demand followed the trends that were given. Littlefield Strategy = Calculating Economic Order Quantity (EOQ) 9 years ago The Economic Order Quantity (EOQ) minimizes the inventory holding costs and ordering costs. For assistance with your order: Please email us at textsales@sagepub.com or connect with your SAGE representative. Using demand data, forecast (i) total demand on Day 100, and (ii) capacity (machine) requirements for Day 100. Demand rate (orders / day) 0 Day 120 Day 194 Day 201. Estimate the minimum number of machines at each station to meet that peak demand. 7 Pages. 25000 By getting the bottleneck rate we are able to predict which of the station may reach full utilization ahead of others and therefore needed more machines to cover the extra load of work to keep the utilization high but not at the peak of 100%. tudents gain access to this effective learning tool for only $15 more. , Georgia Tech Industrial & Systems Engineering Professor. Initially we set the lot size to 3x20, attempting to take advantage of what we had learned from the goal about reducing the lead-time and WIP. In gameplay, the demand steadily rises, then steadies and then declines in three even stages.