However, it was because we did not create a safety margin for production which came from our over estimating our carrying costs. 105 Pennsylvania State University 169 We used to observe revenues. This time, they would like your help with further lead time improvements and optimizing their inventory policy. One focus of ours during this simulation was minimizing the cost of inventory orders and stock outs. Specifically we were looking for upward trends in job arrivals and queue sizes along with utilizations consistently hitting 100%. 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. The sales revenue decreased from 9 million to 6 million in 12 years and also they incurred operating losses. Simulation & Gaming. Project As such, the first decision to be made involved inventory management and raw material ordering. Despite this, not many teams were aware about what had to be done exactly - which I think hurt their chances. Figure 1: Day 1-50 Demand and Linear Regression Model pratt10. Capacity Management at Littlefield Technologies Our strategy was to get lead times down below .5 days and offer customers that lead time to maximize revenue. View Assessment - Littlefield_1_(1).pptx from MS&E 268 at Stanford University. Jaimin Patel This lasted us through the whole simulation with only a slight dip in revenue during maximum demand. Moreover, my research reveals that just by reducing 10% of the current workforce and decreasing the wheel loader system from 10 to 9 would allow us to reach above projected savings. The disadvantage with this approach is that it consumes a lot of time - the time, which runs at a rapid pace of three simulation days per minute. Hence, we will increase our capacity levels where demand is forecasted to peak. 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 products 268-day lifetime). But we did not know if it was the reason for the full utilization of the machinery. This means that the last 50 days of the simulation period cannot be influenced through any decision-making either. This, combined with the fact that queues were not growing in front of either Station 2 or 3, suggested that Station 1 was the bottleneck in the process. Private military companies, in contrast to traditional military contractors provide both direct military services and security services. We knew that the initial status quo was limited by the inventory quantity. 137 Marcio de Godoy This article summarizes the nine contributions to the symposium on system dynamics. 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 goal of setting the inventory policies is to avoid inventory stock outs and the decision-making is typically based on ordering the optimum inventory quantity (EOQ) at right reorder-points (ROP) i.e. Preplan should include your strategy for the game and the analysis your group did to arrive at that strategy. Pre-production market research suggested that the average daily demand level would be somewhere between 10 orders/day and 14 orders/day. Your write-up should address the following points: A brief description of what actions you chose and when. My reasoning for using this strategy is that my products will be extremely useful and beneficial to its consumers; products like BIC and McDonalds are in extreme demand with the situation of todays economy. 9, Faculty can choose between two settings: a high-tech factory named Littlefield Technologies or a blood testing service named Littlefield Labs. Whenever revenues reduced, we use to change the scheduling and observe if the revenue problem is resolved. at Littlefield Technologies Spring 2007( Hence, the effective decision-making period is between day-31 to day-309. After resolving the lead-time issues, we used to switch back the contract to contract-3. | Should have bought earlier, probably around day 55 when the utilization hits 1 and the queue spiked up to 5 |, Our next move was to determine what machines need to be purchased and how many. Part 1: Reasoning for Decisions It is necessary to manage mistakes made in strategy during the game, which can resolve issues down the road to have a successful business plan. Therefore, we took aproactive approach to buying machines and purchased a machine whenever utilization rates rose dangerously high or caused long queues. (Exhibit 2: Average time per batch of each station). 57 I was mainly responsible for the inventory . on 54th day. Later however, as the demand increased, it became increasingly complex and difficult for me to predict the annual demands needed for correct EOQ and ROP calculations. Littlefield Simulation. 25000 Going into this game our strategy was to keep track of the utilization for each machine and the customer order queue. 4 | beaters123 | 895,405 | However, observed 100% Utilization at Station #1 with the 17x more queued kits. This proposal, when implemented, can save up to Rs. Thus we decided to change the most pressing variable, inventory, and see where it went from there. After contract 3 was reached, our simulation flowed very well with the maximum amount of profit for almost the full remainder of the simulation. 2. The logic behind this decision was to complete as many units as possible without delay. Clipping is a handy way to collect important slides you want to go back to later. To account for the unpredictability in demand and the possibility of getting many consecutive high demand days, we stayed with a reorder point greater than our estimate. The winning team is the team with the most cash at the end of the game (cash on hand less debt). Day 53 Our first decision was to buy a 2nd machine at Station 1. TIA. Starting at 5 PM on Wednesday, February 27, the simulation will begin The game will end at 9 PM on Sunday, March 3. Our team finished the simulation in 3rd place, posting $2,234,639 in cash at the end of the game. This taught us to monitor the performance of the, machines at the times of very high order quantities when considering machine. The SlideShare family just got bigger. Analysis of the First 50 Days Current State of the System and Your Assignment 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. Can you please suggest a winning strategy. They want your team to look into why this is occurring, and hopefully remedy the situation. . They include five articles on basic research in learning and teaching principles for system dynamics, three articles on interactive learning, Purpose This helped us focus more on our individual areas. Uploaded by zilikos. highest profit you can make in simulation 1. Purchasing Supplies ROI=Final Cash-Day 50 Cash-PP&E ExpenditurePP&E Expenditure 1,915,226-97,649-280,000280,000=549% By doing so we have a Gross profit of $1,125,189, |production increase. We bought additional machines at stations with high utilization rates in an attempt to relieve those bottlenecks. Global negotiations to reduce greenhouse gas (GHG) emissions have so far failed to produce an agreement. With the daily average demand and SD we could control the Littlefield Labs system capacity. [pic] |BOSTON By doing so, the labor costs are significantly reduced and the unit demand will be covered. This was determined by looking at the rate of utilization of the three machines and the number of jobs in the queue waiting for these machines. Out of these five options, exponential smoothing with trend displayed the best values of MSE (2.3), MAD (1.17), and MAPE (48%). In the beginning of the simulation itself, we had decided to be proactive in lead-time management and hence go for the aggressive contracts. 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. 25 The goal of the symposium is to investigate how research in system dynamics is contributing to simulation-gaming, and how the more general field of simulation-gaming is influencing work in system dynamics. Features Bring operations to life with the market-leading operations management simulation used by hundreds of thousands! Shortly after day 50, we switched to the contract-2. Chu Kar Hwa, Leonard Managements main concern is managing the capacity of the factory in response to the complex demand pattern. In the game, teams are . In addition, because the factory is essentially bootstrapping itself financially, management is worried about the possibility of bankruptcy. In early January 2006, Littlefield Technologies (LT) opened its first and only factory to produce its newly developed Digital Satellite System (DSS) receivers. 9. match. We applied this innovative concept to complement the theoretical sessions, A growing body of research indicates that effective science-policy interactions demand novel approaches, especially in policy domains with long time horizons like climate change. Second, we controlled the inventory level with finding right QOPT (Optimal Order Quantity) and reorder point according to continuous review system method. I then multiplied that by the obvious 60 minutes per hour to determine the output from each machine center each hour. Management requires a 10% rate of return on its investments. We did not have any analysis or strategy at this point. Day 53 Our first decision was to buy a 2nd machine at Station 1. In November we hire 7 employees due to the increase of Holiday sales, and in December we hire 6 employees. To ensure we are focused and accomplish these set goals, the following guidelines Running head: Capacity Management By accepting, you agree to the updated privacy policy. 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. 1 | bigmoney1 | 1,346,320 | ev Revenue 1 241 The account includes the decisions we made, the actions we took, and their impact on production and the bottom line. We did less messing around with the lot size and priority since these were definitely less important to the overall success of your factory than the number of machines you had. The five options for cost cutting are reducing agency staff, downsizing staff, reducing benefits, changing the skill mix, and reducing length of stay for the patients. On day 97, we changed Station 2s scheduling rule to priority step 2. Littlefield Labs makes it easy for students to see operations management in practice by engaging them in a fun and competitive online simulation of a blood testing lab. However, to reduce holding costs and ordering costs t [ As our contracts changed, our lead times changed the problem of inventory reorder points ] After we signed to contract 3, we made few changes to the factory. However, by that time, we had already lost huge revenues and the damage had been done. Demand is then expected to stabilize. 233 Our revenue per day improved to 200 $/day. The decision for the customer contract is between three options. 15 Why? By doing this, we could produce all incoming kits with a priority enabling an even flow of kits to Station 3. 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. Overall results and rankings. Customer demand continues to be random, but the long-run average demand will not change over the product 486-day lifetime. The goal of our company was to make money, so we needed to upgrade to contract 3 as quickly as possible. One key element that caught my attention was bottleneck issues. Day 50 Group Report 1: Capacity Management The following is an account of our Littlefield Technologies simulation game. These key areas will be discussed throughout the journal to express my understanding of the experience. 0 6 comments Best Add a Comment camcamtheram 2 yr. ago Littlefield Laboratories has opened a new blood testing lab. Littlefield Simulation Section 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. Clear role definitions avoid confusion and save time. At the same time, the queue in front of Station 2 was growing, which was odd as the machine was not completely utilized. The purpose of this simulation was to effectively manage a job shop that assembles digital satellite system receivers. Ranking This decision was taken based on a demand of 91 jobs and a utilization of station 1 of 0.83 between days 143 and, After the initial observations of demand for littlefield labs (day 52), one of the first steps we took was to identify the bottleneck in the production chain. 1. Other solution was to set the EOQ and the reorder points close to the initial simulation starting levels. We have reinforced many of the concepts and lessons learned in class and had a better understanding of the operation of the Littlefield Technologies facility and how certain modifications would affect the throughput and lead time. 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. We wanted machine 3 to never be idle and thus, kept the priority at 2. Report on Littlefield Technologies Simulation Exercise Summary of articles. A collaborative backcasting game, AudaCITY, developed to build transformative capacity in city administrations while also generating deep contextual knowledge to inform a transformative sustainability science research agenda is presented. stuffing testing Upon initial analysis of the first fifty days of operations, the team noticed that Station 1 had reached 100% utilization several times between days 40 and 50. Do not sell or share my personal information, 1. . We knew that we needed to increase capacity and the decision was made to purchase another machine 1., BIC is a product that has been extremely successful, offering items such as a low-cost disposable razor, and pens that add value to the user at an affordable price. We then determined our best course of action would be to look at our average daily revenue per job (Exhibit 7) and see if we could identify any days when that was less than the maximum of $1,000/job, so we could attempt to investigate what days to check on for other issues. Good teamwork is the key. 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. The decision making for the machines is typically based on the utilization of machines. Figure 1: Day 1-50 Demand and Linear Regression Model This project attempts to model this game using system dynamics approach, which allows realistic representation of the production system of Littlefield . to help you write a unique paper. Littlefields management would like to be able to charge the premium prices that customers would be willing to pay for dramatically shorter lead times. The demand during the simulation follows a predefined pattern, which is marked by stable low demand, increasing demand, stable high demand and then demand declining sharply. Serious games offer. Thereafter we kept an active watch on lead-times and tried to resolve it through the intense team communication and proactive operations-management.
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