• Proceedings of the Safety Management and Science Conference
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• 2005.11a
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• pp.194-198
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• 2005

Inventory information system is providing the benefits of smoother demand, lower inventories(work in process, safety stock) and reduced costs. This study focused on improvement of safety level inventory efficiency by inventory information system. The results indicated that inventory information system allowed the company to serve its customers more surely and efficiently.

• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.271-277
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• 1999

In this paper, a case study is introduced on the development of an inventory management system for the textile industry. For the low-cost and high-efficient production, a systematic management is needed from make-to-order to delivery. In this paper, an integrated inventory management system for the D company is developed to manage the whole information related with make-to-order, production, delivery, and inventory, and so forth.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.30 no.3
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• pp.117-126
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• 2007

It has been a major issue to repair the broken system quickly for improvement of productivity and utilization. Generally, high utilization of system requires the high amount of spare parts in inventory and inventory cost. Therefore, it is necessary to determine the proper amount of inventory with regard to utilization of system. This study designs a methodology for determining the proper amount of inventory level in a two-echelon spare parts distribution system. The requirements are to satisfy proper customer demands at a distribution center and to maintain over the utilization of the whole system at customers. This methodology minimizes total inventory investment at a distribution center and customers.

• The Journal of Information Systems
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• v.6 no.1
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• pp.223-256
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• 1997

Since the business scales of retailing companies become to be very large and the number of items dealt increases explosively, automation of inventory management becomes one of the most important issues to solve in retailing industry. In order to accomplish this automation of inventory management, there must be a great need to a method which can perform real-time decision making on inventory control in an automatic fashion, while communicating with inventory information systems like POS system and automatic warehousing system. But even in this circumstance, there are also many obstructions to such automation like varying demands, limited capacity of warehouse and exhibition room, need for strategic consideration on inventory control, etc., in a real sense. Due to these reasons, it seems very difficult that most large-scaled retailing companies get fully automated inventory management system. To overcome those difficulties and reflect them into inventory control, we propose a automated inventory control methodology for retailing industry based on neural network and policy model. Especially, policy model is devised to deal with dynamic varying demands and using this model, strategic goals on inventory can be considered into inventory control mechanism. Our proposed approach is implemented in workstation and its performance is also empirically verified also against to real case of one of the major retailing firm in Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.2
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• pp.515-528
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• 2012

The aim of this article is to provide a study on the issue of inventory inaccuracy and to show the manner in which RFID technology can improve the inventory management performance. The objective of inventory control is to monitor the stock flow of merchandises in order to understand the operating profit and loss. A proper mechanism of inventory control could be made to help the profitability. As RFID is applied to inventory control, it can improve efficiency, enhance accuracy and achieve security. In this paper, we introduce the evolution of different mechanisms of inventory control with RFID system-counting method, collect-all method, and continuous monitoring method. As for improving the accuracy of inventory check during business hours, continuous monitoring is the solution. We introduce the infrastructure of the RFID inventory management system based on M2M architecture can make the inventory be efficiently monitored with instant warnings.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.584-590
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• 2001

An inventory management system of manufacturing industry has a model of different kinds according to the objective and the situation. An inventory management system needs superior system technique in demand forecast, economical efficiency, reliability and application for stable supply of the finished goods, the raw materials and the parts. This paper proposes a demand forecast method based on fuzzy structured neural network, which uses min-operation and trapezoid membership function of fuzzy rules. So we can construct an intelligent inventory management system that make optimized decision-making for forecasting data with expert s opinion in fuzzy environment. The inventory management system uses intelligence agent and it could be adapted to a system environment change in order.

• Journal of the military operations research society of Korea
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• v.28 no.2
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• pp.1-19
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• 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 information and communication convergence engineering
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• v.19 no.4
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• pp.221-227
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• 2021

An early warning system was developed to help identify stock status as early as possible. For performance to improve, there needs to be a feature to predict the amount of stock that must be provided and a feature to estimate when to buy goods. This research was conducted to improve the inventory early warning system and optimize the Reminder Block's performance in minimum stock settings. The models used in this study are the single exponential smoothing (SES) method for prediction and the economic order quantity (EOQ) model for determining the quantity. The research was conducted by analyzing the Reminder Block in the early warning system, identifying data needs, and implementing the SES and EOQ mathematical models into the Reminder Block. This research proposes a new Reminder Block that has been added to the SES and EOQ models. It is hoped that this study will help in obtaining accurate information about the time and quantity of repurchases for efficient inventory management.

• The Journal of Information Systems
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• v.30 no.1
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• pp.151-177
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• 2021

Purpose This paper aims to improve management performance by effectively responding to production needs and reducing inventory through synchronizing production planning and procurement in the aviation industry. In this study, the differences in production planning and execution were first analyzed in terms of demand, supply, inventory, and process using the big data collected from a domestic aircraft manufacturers. This paper analyzed the problems in procurement and inventory management using legacy big data from ERP system in the company. Based on the analysis, we performed a simulation to derive an efficient procurement and inventory management plan. Through analysis and simulation of operational data, we were able to discover procurement and inventory policies to effectively respond to production needs. Design/methodology/approach This is an empirical study to analyze the cause of decrease in inventory turnover and increase in inventory cost due to dis-synchronize between production requirements and procurement. The actual operation data, a total of 21,306,611 transaction data which are 18 months data from January 2019 to June 2020, were extracted from the ERP system. All them are such as basic information on materials, material consumption and movement history, inventory/receipt/shipment status, and production orders. To perform data analysis, it went through three steps. At first, we identified the current states and problems of production process to grasp the situation of what happened, and secondly, analyzed the data to identify expected problems through cross-link analysis between transactions, and finally, defined what to do. Many analysis techniques such as correlation analysis, moving average analysis, and linear regression analysis were applied to predict the status of inventory. A simulation was performed to analyze the appropriate inventory level according to the control of fluctuations in the production planing. In the simulation, we tested four alternatives how to coordinate the synchronization between the procurement plan and the production plan. All the alternatives give us more plausible results than actual operation in the past. Findings Based on the big data extracted from the ERP system, the relationship between the level of delivery and the distribution of fluctuations was analyzed in terms of demand, supply, inventory, and process. As a result of analyzing the inventory turnover rate, the root cause of the inventory increase were identified. In addition, based on the data on delivery and receipt performance, it was possible to accurately analyze how much gap occurs between supply and demand, and to figure out how much this affects the inventory level. Moreover, we were able to obtain the more predictable and insightful results through simulation that organizational performance such as inventory cost and lead time can be improved by synchronizing the production planning and purchase procurement with supply and demand information. The results of big data analysis and simulation gave us more insights in production planning, procurement, and inventory management for smart manufacturing and performance improvement.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2007.05a
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• pp.198-208
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• 2007

Recently business enterprises have forced to face in fierce competition in today's global markets due to the short life cycles of products and the higher expectation of customers. Together with continuing advances in communications and transportation technologies, these environments have motivated the continuous evolution of the supply chain and the management techniques. This paper consider three-echelon inventory system which consist of one manufacturer, one distributor and N retailers for a single product under assumption of constant demand. This paper propose the inventory replenishment period using heuristic method and order policy through coordination of inventory replenishment period. The simulation results show that decrease the total cost of the three-echelon inventory system.