• Journal of the military operations research society of Korea
• /
• v.28 no.2
• /
• pp.1-19
• /
• 2002

This study shows the effect of inventory policy change from supplier-based to customer-based. We focus on the service level, cost, and information distortion of the Military Supply Chain(MSC) with System Dynamics. We design MSC model according to field practician interviews by using Vensim. The simulation makes a comparison between supply-based inventory policy performances and order-based inventory policy performances. In order to evaluate the MSC performances, we measure the accumulation of backlog(service level), supply chain cost, and order percentage overshoot(information distortion). The results show that 1) changing inventory policy from supplier-based to end customer order-based gets a good customer service, reduces MSC cost, and prevents information distortion, 2) changing inventory policy from supplier-based to immediate customer order-based reduces a small amount of MSC cost and deteriorates customer service, and 3) supply level is main factor for MSC performances improvement. This study implicates the policy change makes a improvement of MSC performance without introducing information system.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.37 no.2
• /
• pp.45-56
• /
• 2012

This paper considers a supply chain consisting of a component manufacturer and a product manufacturer. The component manufacturer provides components for the product manufacturer based on a vendor-managed inventory type of supply contract, and also faces demands from the market with the option of to accept or reject each incoming demand. Using the Markov decision process model, we examine the structure of the optimal production control and inventory rationing policy. Two types of heuristics are presented. One is the fixed-buffer policy and the other uses two linear functions. We implement a computational study and present managerial insights based on the observations.

• Journal of the Korea Safety Management & Science
• /
• v.6 no.3
• /
• pp.141-152
• /
• 2004

Supply chains for agricultural commodities with their various constraints such as production lead time, seasonal production, and methods of storage are limited in the extent to which techniques like Just-in-Time (JIT) inventory management can be applied. It is beyond the ability of producers to control harvest time and many agricultural products are perishable so that they can incur exceptional losses in storage if they are not handled correctly. This is a source of additional costs and inefficiency in supply chain management. The purpose of this study is to reduce or eliminate such sources of loss and inefficiency and to identify success factors for the JIT inventory management system where it can be applied for agricultural products. Where JIT techniques can be applied in supply chain management for agricultural products, costs such as transportation, inventory, and storage losses can be reduced with concurrent increases in efficiency. In the paper, some of the problems associated with applying JIT inventory control methods in supply chain management for agricultural commodities will be reported through a series of case studies.

• Proceedings of the Safety Management and Science Conference
• /
• 2004.05a
• /
• pp.191-201
• /
• 2004

Supply chains for agricultural commodities with their various constraints such as production lead time, seasonal production, and methods of storage are limited in the extent to which techniques like Just-in-Time (JIT) inventory management can be applied. It is beyond the ability of producers to control harvest time and many agricultural products are perishable so that they can incur exceptional losses in storage if they are not handled correctly. This is a source of additional costs and inefficiency in supply chain management. The purpose of this study is to reduce or eliminate such sources of loss and inefficiency and to identify success factors for the JIT inventory management system where it can be applied for agricultural products. Where ]IT techniques can be applied in supply chain management for agricultural products, costs such as transportation, inventory, and storage losses can be reduced with concurrent increases in efficiency. In the paper, some of the problems associated with applying ]IT inventory control methods in supply chain management for agricultural commodities will be reported through a series of case studies.

• Journal of the Korea Society for Simulation
• /
• v.12 no.4
• /
• pp.61-71
• /
• 2003

Recently, a matter of the highest priority that the company must do for the satisfaction of customer service is that the company ensure the competitive power throughout the strategic cooperation in the market environment changing rapidly In this situation, one of allied strategies is the supply chain management and the outsourcing is one of the supply chain management strategies. In this paper, the inventory sharing system is introduced as the method to solve two inconsistency problem such as inventory and customer service. This paper also suggests how to increase customer service and to decrease inventory throughout construction of the inventory sharing system among outsourcing companies. For this, we experimented the effect of the inventory sharing system on the supply chain dynamics by using the simulation modeling and analyzed the validity about construction of the inventory sharing system presented in this study. The simulation is designed by Vensim(Process simulation package) and has some feedback loops.

• Industrial Engineering and Management Systems
• /
• v.8 no.2
• /
• pp.80-92
• /
• 2009

This paper addresses the inventory rationing issue embedded in the regional supply chain inventory replenishment problem (RSIRP). The concerned supply chain, which was fed by the national supply chain, consisted of a single warehouse distributing a single product to multiple stores (M-stores) with independent and normally distributed customer demand. It was assumed that the supply chain operated under the order-up-to level inventory replenishment system and had only one truck at the regional warehouse. The truck could make one replenishment trip to one store per period (a round trip per period). Based on current inventories and the vehicle constraint, the warehouse must make two decisions in each period: which store in the region to replenish and what was the replenishment quantity? The objective was to position inventories so as to minimize lost sales in the region. The warehouse inventory was replenished in every fixed-interval from a source outside the region, but the store inventory could be replenished daily. The truck destination (store) in each period was selected based on its maximum expected shortage. The replenishment quantity was then determined based on the predetermined order-up-to level system. In case of insufficient warehouse inventories to fulfill all projected store demands, an inventory rationing rule must be applied. In this paper, a new inventory rationing rule named Expected Cost Minimization (ECM) was proposed based on the practical purpose. The numerical results based on real data from a selective industry show that its performance was better and more robust than the current practice and other sharing rules in the existing literature.

• Journal of Korean Institute of Industrial Engineers
• /
• v.31 no.2
• /
• pp.106-119
• /
• 2005

Uncertainties inherent in customer demand patterns make it difficult for supply chains to achieve just-in-time inventory replenishment, resulting in loosing sales opportunity or keeping excessive chain wide inventories. In this paper, we propose two intelligent adaptive inventory control models for a supply chain consisting of one supplier and multiple retailers, with the assumption of information sharing. The inventory control parameters of the supplier and retailers are order placement time to an outside source and reorder points in terms of inventory position, respectively. Unlike most extant inventory control approaches, modeling the uncertainty of customer demand as a stationary statistical distribution is not necessary in these models. Instead, using a reinforcement learning technique, the control parameters are designed to adaptively change as customer demand patterns change. A simulation based experiment was performed to compare the performance of the inventory control models.

• Journal of Korean Institute of Industrial Engineers
• /
• v.30 no.3
• /
• pp.197-204
• /
• 2004

This paper deals with a supply chain with a company and its contractor that produces products by the OEM contract with the company. The supply chain of interest has two distinct features. First, the company is the supplier of raw material required in the production at the contractor. Second, the company and its contractor make a delivery shipment arrangement that the replenishment lead time is determined depending on demand process. We show that the optimal inventory policy is monotonically changed as either the replenishment setup cost or inventory holding cost becomes increased or decreased. We also present asymptotic properties of the optimal inventory policy when either the number of outstanding customer orders or the inventory level becomes very large.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.3
• /
• pp.77-88
• /
• 2021

The development history of China's big data is relatively short, and it has only been ten years so far. Although the application level of big data in real life is not high, some achievements have been made in the supply chain. Various kinds of data will be generated in the actual operation of the supply chain. If these data can be effectively classified and used, the "bullwhip effect" of the operation of the supply chain can be also effectively improved. Thus this paper proposes the development of a supply chain collaborative inventory management model and application framework using big data. In this study, we analyzed the supply chain of beer industry, which is the most prominent consumption industry with "bullwhip effect", and further established a big data collaborative inventory management model for the supply chain of beer industry based on system dynamics. We used the Vensim software for simulation and sensitivity test and after appling our model, we found that the inventory fluctuations of the participants in the beer industry supply chain became significantly smaller, which verified the effectiveness of the model. Our study can be also applied to the possible problems of the large data supply chain collaborative inventory management model, and gives certain countermeasures and suggestions.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.37 no.4
• /
• pp.116-125
• /
• 2014

In this paper, we investigate an inventory and production system in a three-layer supply chain system involving a single supplier, single manufacturer and multiple retailers. Earlier study in this type of supply chain only consider a single raw material in order to produce single item, but we consider raw materials in order to produce multiple items. It is assumed that the cycle time at each stage is an integer multiple of the adjacent downstream stage. We develop an iterative solution procedure to find the order quantity for the multiple items and raw materials that minimizes the supply chain-wide total cost per unit time of the supplier and manufacturer's raw materials ordering and holding, setup and finished items holding, the retailer's ordering and inventory holding. Numerical examples are presented to show that the proposed heuristic gives good performance.