H=$0.675 Anise Tan Qing Ye This latest move comes only a month after OPEC sig becomes redundant? We needed to have sufficient capacity to maintain lead times of less than a day and at most, 1 day and 9 hours. 3lp>,y;:Hm1g&`@0{{gC]$xkn WRCN^Pliut mB^ A summary of the rationale behind the key decisions made would perhaps best explain the results we achieved. reorder point and reorder quantity will need to be adjusted accordingly. Features Bring operations to life with the market-leading operations management simulation used by hundreds of thousands! While forecast accuracy is rarely 100%, even in the best of circumstances, proven demand forecasting techniques allow supply chain managers to predict future demand with a high degree of accuracy. : 5 | donothing | 588,054 | 1. The average queues at stations 1 and 3 were reduced. We've encountered a problem, please try again. 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. Our final machine configuration (which was set on Day 67) was 3 machine 1's, 2 machine 2's, and2 machine 3's. change our reorder point and quantity as customer demand fluctuates? Estimate the best order quantity at peak demand. Based on the linear decrease in revenue after a lead time of one day, it takes 9 hours for the revenue to drop to $600 and our profits to be $0. Responsive Learning Technologies 2010. DEMAND FORECASTING AND ESTIMATION We assessed that, demand will be increasing linearly for the first 90 to 110 days, constant till 18o days and then fall of after that. 121 the formula given, with one machines on each station, and the average expected utilization rate, we have gotten the answer that the And the station with the fastest process rate is station two. 5000 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. time contracts or long-lead-time contracts? 9 Managing Capacity and Lead Time at Littlefield Technologies Team 9s Summary Day | Parameter | 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. Open Document. The winning team is the team with the most cash at the end of the game (cash on hand less debt). 0 (98. Home. Next we calculated what Customer Responsiveness Simulation Write-Up specifically for you for only $16.05 $11/page. Purchase a second machine for Station 3 as soon as our cash balance reached $137,000 ($100K + 37K). Thus our inventory would often increase to a point between our two calculated optimal purchase quantities. Course Hero is not sponsored or endorsed by any college or university. Because we hadnt bought a machine at station 1 we were able to buy the one we really needed at station 3. : an American History (Eric Foner), Civilization and its Discontents (Sigmund Freud), Forecasting, Time Series, and Regression (Richard T. O'Connell; Anne B. Koehler), Biological Science (Freeman Scott; Quillin Kim; Allison Lizabeth), Campbell Biology (Jane B. Reece; Lisa A. Urry; Michael L. Cain; Steven A. Wasserman; Peter V. Minorsky), Chemistry: The Central Science (Theodore E. Brown; H. Eugene H LeMay; Bruce E. 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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 B6016 Managing Business Operations Littlefield is an online competitive simulation of a queueing network with an inventory point. Littlefield is an online competitive simulation of a queueing network with an inventory point. We forecast demand to stay relatively stable throughout the game based on . The following equation applies to this analysis: Regression Analysis = a + bx After using the first 50 days to determine the demand for the remainder of the 593 0 obj<> endobj 0000000649 00000 n Author: Zeeshan-ul-hassan Usmani. 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. After this, demand was said to be declined at a linear rate (remaining 88 days). tuning Specifically we were looking for upward trends in job arrivals and queue sizes along with utilizations consistently hitting 100%. Furthermore, we thought that buying machines from Station 3 was unnecessary because of the utilization in that station. 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. There are two main methods of demand forecasting: 1) Based on Economy and 2) Based on the period. Thus we wanted the inventory from station 1 to reach station 3 at a rate to effectively utilize all of the capability of the machines. And then we applied the knowledge we learned in the . Faculty can choose between two settings: a high-tech factory named Littlefield Technologies or a blood testing service named Littlefield Labs. the operation. From that day to day 300, the demand will stay at its peak and then start dropping 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. Explanations. Next we, calculated what game it would be in 24 hours, and then we, plugged that into the linear regression to get the mean, forecasted number of orders on that day. In addition, because the factory is essentially bootstrapping itself financially, management is worried about the possibility of bankruptcy. According to Holt's exponential model we forecast the average demand will be 23, by using @littledashboard / littledashboard.tumblr.com. If the order can be completed on-time, then the faster contract is a good decision. However, when . A discussion ensued and we decided to monitor our revenue on this day. The information was used to calculate the forecast demand using the regression analysis. 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. This was necessary because daily demand was not constant and had a high degree of variability. We took the sales per day data that we had and calculated a liner regression. The first step in the process is investigating the company's condition and identifying where the business is currently positioned in the market. Revenue maximization:Our strategy main for round one was to focus on maximizing revenue. Initial Strategy Definition About Press Copyright Contact us Creators Advertise Developers Terms Privacy Policy & Safety How YouTube works Test new features Press Copyright Contact us Creators . 0000003038 00000 n 0000001293 00000 n Within the framework of all these, our cash balance was $120,339 at the end of the game, since we could not sell those machines and our result was not quite good as our competitors positions. maximum cash balance: In addition, the data clearly showedprovided noted that the demand was going to follow an increasing trend for the initial 150 days at least. The forecast bucket can be selected at forecast generation time. The available values are: Day, Week, and Month. Starting at 5 PM on Wednesday, February 27, the simulation will begin The game will end at 9 PM on Sunday, March 3. 7 Pages. 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Status and Forecast 2025 - This report studies the global . Starting off we could right away see that an additional machine was required at station 2 to handle . Learn faster and smarter from top experts, Download to take your learnings offline and on the go. Littlefield Simulation Kamal Gelya. Question 1 Demand Forecasting We were told that demand would be linearly increasing for the first 90-110 days, constant till day 180 and then fall off after that. ROP. 25000 change our reorder point and quantity as customer demand fluctuates? S: Ordering cost per order ($), and Littlefield Simulation Report Question Title * Q1. 209 113 What are the key insights you have gained from your work with the simulation; 2. 24 hours. Looking at our Littlefield Simulation machine utilization information from the first 50 days, it was fairly easy to recognize the initial machine bottleneck. utilization and also calculate EOQ (Economic Order Quantity) to determine the optimal ordering Tan Kok Wei 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. Let's assume that the cost per kit is $2500; that the yearly interest expense is 10%; andy therefore that the daily interest expense is .027%. Different forecasting models look at different factors. 20000 Our assumption proved to be true. Write a strategy to communicate your brand story through: Each hour of real time represents 1 day in the simulation. V8. Why? Regression Analysis: The regression analysis method for demand forecasting measures the relationship between two variables. We calculate the reorder point Survey methods are the most commonly used methods of forecasting demand in the short run. Our final inventory purchase occurred shortly after day 447. 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. We experienced live examples of forecasting and capacity management as we moved along the game. Please create a graph for each of these, and 3 different forecasting techniques. Bring operations to life with the market-leading operations management simulation used by hundreds of thousands! Data was extracted from plot job arrival and analyzed. 5 PM on February 22 . With much anticipation we reviewed all the literate that was provided subsequently to assist us in decision making at Littlefield Technologies. Our team operated and managed the Littlefield Technologies facility over the span of 1268 simulated days. 17 ROI=Final Cash-Day 50 Cash-PP&E ExpenditurePP&E Expenditure 1,915,226-97,649-280,000280,000=549% Going into this game our strategy was to keep track of the utilization for each machine and the customer order queue. . last month's forecast + (actual demand - last month's demand) an additional parameter used in an exponential smoothing equation that includes an adjustment for trend. In particular, if an LittleField By getting the bottleneck rate we are able to predict which of the . Leena Alex Different Littlefield assignments have been designed to teach a variety of traditional operations management topics including: Assignment options include 2-hour games to be played in class and 7-day games to be played outside class. Littlefield Simulation Report Essay Sample. We tried not to spend our money right away with purchasing new machines since we are earning interest on it and we were not sure what the utilization would be with all three of the machines. We used the demand forecast to plan machinery and inventory levels. I know the equations but could use help finding daily demand and figuring it out. xbbjf`b``3 1 v9 Operations Policies at Littlefield Technologies Assignment Stage 2 strategy was successful in generating revenue quickly. Which of the. Demand forecasting has the answers. 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. Based on our success in the last Littlefield Simulation, we tried to utilize the same strategy as last time. Each customer demand unit consists of (is made from) 60 kits of material. 7 Pages. Team Pakistan As we see in an earlier post about predicting demand for the Littlefield Simulation, and its important to remember that the predicted demand and the actual demand will vary greatly. Cash Balance Our team operated and managed the Littlefield Technologies facility over the span of 1268 simulated days. Littlefield Simulation Overview Presentation 15.760 Spring 2004 This presentation is based on: . In this case, all customers (i.e., those wishing to place. When this was the case, station 1 would feed station 2 at a faster rate than station 3. Political Science & International Relations, Research Methods, Statistics & Evaluation, http://ed.gov/policy/highered/leg/hea08/index.html, CCPA Do Not Sell My Personal Information. Sense ells no existirem. There are 3 stations in the game called sample preparing, testing, and centrifuging, while there are 4 steps to process the jobs. Problems and issues-Littlefield Technologies guarantee-Forecasted demand . Not a full list of every action, but the June The . We tried not to spend our money right away with purchasing new machines since we are earning interest on it and we were not sure what the utilization would be with all three of the machines. West University Blvd., Melbourne, FL . Littlefield Strategy = Calculating Economic Order Quantity (EOQ) 9 years ago The Economic Order Quantity (EOQ) minimizes the inventory holding costs and ordering costs. You can read the details below. 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. We, than forecasted that we would have the mean number of, orders plus 1.19 times the standard deviation in the given, day. endstream endobj 594 0 obj<>>>/LastModified(D:20040607164655)/MarkInfo<>>> endobj 596 0 obj<>/Font<>/XObject<>/ProcSet[/PDF/Text/ImageC/ImageI]/ExtGState<>/Properties<>>>/StructParents 0>> endobj 597 0 obj<> endobj 598 0 obj[/Indexed 607 0 R 255 608 0 R] endobj 599 0 obj<> endobj 600 0 obj<> endobj 601 0 obj<>/PageElement<>>>>> endobj 602 0 obj<>stream 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 . LITTLEFIELD TECHNOLOGIES Do not sell or share my personal information, 1. 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 used demand forecast to plan purchase of our, machinery and inventory levels. We did intuitive analysis initially and came up the strategy at the beginning of the game. 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). Now customize the name of a clipboard to store your clips. cost for each test kit in Simulation 1 &2. For the short time when the machine count was the same, stations 1 and 3 could process the inventory at a similar rate. A new framework for the design of a dynamic non-myopic inventory and delivery network between suppliers and retailers under the assumption of elastic demandone that simultaneously incorporates inventory, routing, and pricingis proposed. Weve updated our privacy policy so that we are compliant with changing global privacy regulations and to provide you with insight into the limited ways in which we use your data. The regression forecasts suggest an upward trend of about 0.1 units per day. we need to calculate capacity needs from demand and processing times. Littlefield Simulation Report: Team A Average Daily Demand = 747 Kits Yearly Demand = 272,655 Kits Holding Cost = $10*10% = $1 EOQ = sqrt(2DS/H) = 23,352 Kits Average Daily Demand = 747 Kits Lead Time = 4 Days ROP = d*L = 2,988 99% of Max. Initially we didnt worry much about inventory purchasing. In terms of choosing a priority Responsiveness at Littlefield Technologies The game can be quickly learned by both faculty and students. By whitelisting SlideShare on your ad-blocker, you are supporting our community of content creators. increase the capacity of step 1. Contact 525 South Center St. Rexburg, ID, 83460 (208) 496-1411 [email protected] Feedback; Follow Facebook Twitter Youtube LinkedIn; Popular . on demand. We have first calculated the bottleneck rate for each station before the simulation started. Executive Summary. You can find answers to most questions you may have about this game in the game description document. 1. Which station has a bottleneck? %%EOF 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. 217 Management's main concern is managing the capacity of the lab in response to the complex . highest profit you can make in simulation 1. For questions 1, 2, and 3 assume no parallel processing takes place. That will give you a well-rounded picture of potential opportunities and pitfalls.