Logistic Management with Beer Game Simulation Wholesaler (Lead Time One Week)

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1 Volume 119 No , ISSN: (on-line version) url: Logistic Management with Beer Game Simulation Wholesaler (Lead Time One Week) Abdurrozzaq Hasibuan 1, Lutfhi Parinduri 1, Oris Krianto Sulaiman 1, Nuning Kurniasih 2, Tri Listyorini 3, Dahlan Abdullah 4, Asmara Indahingwati 5, Kundharu Saddhono 6, Rosida Tiurma Manurung 7, Heri Nurdiyanto 8, Muh Barid Nizarudin Wajdi 9 1 Faculty of Engineering, Universitas Islam Sumatera Utara Medan, Indonesia 2 Faculty of Communication Sciences, Library and Information Science Program, Universitas Padjadjaran Bandung- Indonesia 3 Informatics Engineering, Universitas Muria Kudus 4 Department of Informatics, Universitas Malikussaleh, Aceh, Indonesia 5 Management Science, School of Economics Indonesia"STIESIA" Surabaya, Indonesia 6 Graduate Program, Universitas Sebelas Maret 7 Graduate Program in Scientific Psychology, Universitas Kristen Maranatha 8 Department of Informatics Engineering, STMIK Dharma Wacana 9 STAI Miftahul Ula Nganjuk rozzaq@uisu.ac.id, luthfi.p@ft.uisu.ac.id, oris.ks@ft.uisu.ac.id, nuning.kurniasih@unpad.ac.id, trilistyorini@umk.ac.id, dahlan@unimal.ac.id, asmaraindahingwati@stiesia.ac.id, kundharu.uns@gmail.com, rosida.tm@psy.maranatha.edu, herinurdiyanto@gmail.com, baridnizar84@gmail.com Abstract In this simulation, inventory evaluation is performed at fixed intervals ie weekly. Since the order from the retailer is unpredictable afnd the distributor's ability to meet the wholesaler is unknown, the wholesaler's order which is the input of the game is done by "Trial and Error" in such a way that it is expected to provide a minimum total inventory cost. Although done trial and error, the ordering is done taking into account the current inventory, the incoming order and the number of unmet requests in the previous period. During the simulation period, in an effort to meet the demand that comes, each I. INTRODUCTION In Beer Game this simulation, depicted a simple supply chain consisting of only one factory, one distributor, one wholesaler and one retailer. It is assumed that the plant has unlimited raw materials, and each member of the chain has unlimited storage capacity. Lead time of delivery of goods and delay time for order is fixed[1] [3]. member of the chain to order to suppliers. To get this order to suplier takes 1 week. Once the order is received, the supplier will endeavor to fulfill its inventory. In this case, it takes an additional 2 weeks for order delivery until receipt of order. In this game, it appears that between each member of the supply chain does not occur mutual communication. Therefore, each level performs its own discretion that causes the total cost in the system to be large. Keywords Supply Chain, The Beer Game Simulation Each member in the supply chain is trying to meet the weekly demand of the customer below. All orders must be fulfilled. An unassignable order is considered a backorder and must be met as soon as possible[4] [8]. For each backorder unit, each member of the chain will be charged a $ 1 deficit. To anticipate fluctuating demand, each member of the chain has a storage cost of $ 0.5 per unit. 2611

2 During the simulation period, in an effort to meet the demand that comes, each member of the chain to order to suppliers. To get this order to supplier takes 1 week[9], [10]. Once the order is received, the supplier will endeavor to fulfill its inventory. In this case, it takes an additional 2 weeks for order delivery until receipt of the order. Goal from retailers, wholesalers, distributors, and factories is the total cost minimization, either the cost of each or the cost in the system[11]. In this simulation, Group III acts as a wholesaler. Therefore, things to consider are related to the demand coming from the retailer and the distributor's ability to fulfill the order. As mentioned earlier, the time required until the order received by the distributor is 1 week. Furthermore, if the supply on the part of the distributor is sufficient, then the delivery time of goods until received is 2 weeks[12] [14]. However, if the distributor does not have inventory, then the distributor takes 1 week orders received by the factory. When the product inventory at the factory fulfills, the manufacturer will send the order to the distributor and takes 2 weeks of order receiver[15]. The results of 25 weeks of simulation on Wholesaler can be seen in table 1 and 2. Fig 1. Supply Chain in Beer Game Simulation Table 1. Condition of Inventory on Wholesaler of Simulation Results Week Facing Order Supplied Back order Released order Received Stock on hand Table 2. Inventory and Backorder Costs on Wholesaler Simulation Results Week Back order Inventory Shipped to retailer Stock on hand Accumulated Total Cost From Table 1 and 2, we can see the simulation results for 25 weeks at wholesaler. Table 2 shows the total cost inventory of $ 317. A series of simulation results covering inventory conditions and reporting of all systems in the supply chain are presented in Figures 2, 3, 4 and 5. Fig 3. Report All Systems at the End of Week 25 Fig 2. Inventory Condition and Total Cost at the End of Week 25 In Figure 3 can be seen the average order of 5.84 units with a standard deviation of 4.00 units. When compared with the results on retailers with an average order of 5.56 units and standard deviation of 3.21 units, the value is not much different. Furthermore, in Figure 4 it can be seen that from week to week the order chart of the wholesaler almost coincides with the retailer's order graph. This indicates that the 2612

3 order made by the retailer against the wholesaler is responded by the wholesaler by ordering the distributor. However, because of the inventory owned by the distributor, the order is not always directly able to be filled distributor (going backorder). The backorder has increased the value of week 3 and peak at week 10. Backorder is actually not because of the inability wholesaler set its order. However, due to the inability of the distributor to meet the demand from the wholesaler. This can be seen in table 1 where on the 3rd week until the 9th week, there is a backorder on distributor. Total cost from week to week is clearly an increase, as it is cumulative. The highest cost graph gradient is found in the 3rd to 11th weeks. This situation occurs because in those weeks, there is a high enough backorder causing high total cost. II. RESULT AND DISCUSSION Fig 4. Order Chart (Order) Entire SC System From Figures 3 and 4, we see that the orders are fluctuating with certain standard deviations from all supply chain members. Retailers have the smallest order fluctuations, followed by wholesaler, distributor, factory. There is a tendency that the farther away from the end-consumer of the order it does fluctuate (the standard deviation is greater than the average) and the total cost is also higher. This is understandable, considering that the orders made by the factory are goods procurement activities where the decision to make the goods also considers Set-up costs and so the factory will only produce in economies of scale. From the graph of figure 4. it can be seen that the order done by factory only happened on the 4th week until the 9th week with the number of orders per week 30 units and at the 10th week of 28 units. These conditions also affect the order made by the distributor. Fig 5. Graph Number of Inventory, Backorder, Order and Total Cost for Wholesaler In Figure 5 above information about the condition of the wholesaler. Increased inventory at 12th week until the 16th week. This happens because of a backorder that has been met, while wholesaler orders can be met directly without backorder. The decision to be taken by the wholesaler is when and how many orders should be made to the distributor. In this game, reservations are made without knowing the conditions of other supply chain members. Retailer needs only known wholesaler at the time of order from retailers to him. The condition of the distributor can only be known when the distributor follow up the order from the wholesaler, whether the entire order can be fulfilled or not. To avoid unmet demand (orders coming from retailers), companies can set high inventory levels. However, this decision will result in high inventory costs. Especially in conditions where high capital costs and product risks are damaged, obsolete and so on are quite high. Conversely, companies can set inventory levels as low as possible. However, this will lead to an increased chance of unmet demand. On the one hand this can lead to customer dissatisfaction, which can result in the flight of customers to the company's competitors. On the other hand, for the company itself, this means the opportunity to earn wasted profits. Therefore, the wholesaler must manage his inventory system so that demand can be met with a minimum total cost. For this purpose to be achieved, the wholesaler shall be able to arrange the order by considering: 1. Estimated demand in the coming period 2. Lead time from distributor 3. Estimate the maximum ability of distributors in fulfilling orders sent In the early stages, the wholesaler must make an estimate of demand in the period to come. If the data is not available, then the demand forecast should be made by the decision maker subjectively. Conversely, when data is available, future demand can be estimated by various methods including time series and causal methods. 1. In the time series method, sales data required in the past. The first step to do is to study the pattern of past data. In this method, it is assumed that the pattern of data in the past will continue for the foreseeable future. In accordance with the data pattern, the appropriate forecasting method is chosen. Furthermore, forecasting using various parameters that must be set. The first results that provide the smallest error rate will be used to forecast future demand. 2613

4 2. In the causal method, future demand forecasts are made based on the variables affecting demand. Future prediction values are used as a basis for inventory planning and activity planning in production activities (for the factory). In this simulation, to obtain this required data, then done several times trial. The results can be seen in Figure 2. Apparently, demand fluctuations are very high and are random and do not indicate a certain trend/pattern. Therefore, the time series method cannot be used. Causal methods cannot be used because variables affecting demand for products are unknown. Furthermore, it is attempted to estimate the probability distribution of demand based on data from the 4 simulation trials. 25 week histogram distribution of demand is presented in Figure 3. These results remain unhelpful in order to forecast future demand. To get the inventory system that is expected to meet the needs of retailers, orders can be done wholesaler with: 1. Fixed quantity (fixed order quantity) In this policy, then the decision to be taken is what is the most economical order rate (Economic Order Quantity, EOQ) and when reorder must be done (RER order Point, ROP). 2. Fixed time intervals (fixed order intervals) If this policy is selected, then the decision to be made is how long the booking period provides the minimum total cost. 3. The number and period of time vary depending on the needs. In this simulation, inventory evaluation is performed at fixed intervals ie weekly. Since the order from the retailer is unpredictable and the distributor's ability to meet the wholesaler is unknown, the wholesaler's order which is the input of the game is done by "Trial and Error" in such a way that it is expected to provide a minimum total inventory cost. Although done trial and error, the ordering is done taking into account the current inventory, the incoming order and the number of unmet requests in the previous period. Although it is not easy to make big order decisions, it is actually very simple because: 1. The supply chain network involves only one member at each level. 2. Lead time between levels is certain. This option can be taken if the booking fee is very low, and there is no problem regarding the supplier's ability to meet the fluctuating demand. Order disposal is done as needed, then: Order quantity released = current order + wholesaler backorder + future order forecast - previous order accumulation. Order performed on the game is preceded by the retailer which is the response of fluctuating market demand. the retailer must be able to predict well the market demand to place orders to wholesalers who can provide a minimum total inventory cost with a certain level of service. The problem in the inventory system is caused by 1. Demand that fluctuates and is probabilistic 2. The ability of the distributor to fulfill the order is not known by the previous wholesaler In actual conditions, this becomes more difficult when lead time is also probabilistic. Among the efforts that can be done to reduce the above problem is to hold a safety stock (safety stock). Total cost = Inventory cost + Backorder cost TC = h * I + b * B Where: H = holding cost $ 0.5/unit I = inventory amount (unit) b = shortage cost $ 1 /unit B = number of back order (unit) In this game, it appears that between each member of the supply chain does not occur mutual communication. Therefore, each level performs its own discretion that causes the total cost in the system to be large. The nature of demand for very random products, will cause various forecasting methods cannot be used. Demand for products is very volatile as indicated by the large standard deviation values, sometimes even greater than the average. In practical terms, such demand is rare for Make to Stock (MTS) corporate products. III. CONCLUSION In supply chain management, chain member inventory planning done without coordination with levels above it and below cannot be done carefully. As a result, the ability of each level to meet the demand of its customers is not guaranteed because it does not know how much is needed, so it cannot be prepared beforehand. Conversely, if all members of the chain are in a coordination is the certainty of fulfillment of demand is better, but the company can hold inventory in the minimum amount. This happens because each member of the chain has been able to prepare the needs of its customers (members of the chain below) before the order is delivered. REFERENCES [1] B. B. S. S. V. R. Raghavan, Srinivasa, Object Oriented Design and Implementation of A Web-enabled Beer Game for Illustrating the Bullwhip Effect in Supply Chains i.. [2] T. Ruël, G., van Donk, D. P., van der Vaart, The beer game revisited: Relating risktaking behaviour and bullwhip effect. Procedings of EurOMA [3] R. Rahim et al., C4. 5 Classification Data Mining for Inventory Control, Int. J. Eng. Technol., vol. 7, no. 2.3, pp. 2614

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