• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.61-67
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• 2020

The fourth industrial revolution encourages manufacturing industry to pursue a new paradigm shift to meet customers' diverse demands by managing the production process efficiently. However, it is not easy to manage efficiently a variety of tasks of all the processes including materials management, production management, process control, sales management, and inventory management. Especially, to set up an efficient production schedule and maintain appropriate inventory is crucial for tailored response to customers' needs. This paper deals with the optimized inventory policy in a steel company that produces granule products under supply contracts of three targeted on-time delivery rates. For efficient inventory management, products are classified into three groups A, B and C, and three differentiated production cycles and safety factors are assumed for the targeted on-time delivery rates of the groups. To derive the optimized inventory policy, we experimented eight cases of combined safety stock and data analysis methods in terms of key performance metrics such as mean inventory level and sold-out rate. Through simulation experiments based on real data we find that the proposed optimized inventory policy reduces inventory level by about 9%, and increases surplus production capacity rate, which is usually used for the production of products in Group C, from 43.4% to 46.3%, compared with the existing inventory policy.

• 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.

• Journal of the military operations research society of Korea
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• v.17 no.1
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• pp.84-104
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• 1991

Up to the present, the evaluation measures in the production and inventory management have been studied under the pre-condition that the costs for major factors(e.g,. cost of carrying inventory, cost of demand shortage) are given easily, although in practice, it is difficult. The case in which multiple participants have a different viewpoints in production and inventory management has not been studied, in spite of its frequent occurrence. This study suggests a production and inventory model with multiple objectives corresponding to major factors and the related interactive algorithm based on the preference structures of participants. The problem can be solved through a weighting vector generated by an interaction with participants. The concept of equity is also used in order to guarantee the reasonable distribution of group utility in determining the individual relative weights of participants. This study includes the reality of the model and the decision process in the production and inventory management.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.313-320
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• 2014

We consider the problem to find economic inventory quantity of a single commodity under stochastic demands and order cancellation. In contrast to the traditional economic production quantity (EPQ) model, we assume that once the amount of inventory reaches to a predetermined level of quantity then the production is not halted but its production speed decreases until the inventory level drops to zero. We establish two probabilistic models representing the behaviors of both the high-production period and low-production period, respectively, and derive the relationship between the level of inventory and costs of production, cancellation, and holding, from which the quantity of economic inventory is obtained.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.1
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• pp.13-34
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• 1991

A production/inventory system is considered in which a production facility produces one type of product. The demand for the product is given by a compound Poison process and is supplied directly from inventory when inventory is available and is lost when inventory is out of stock. The processing time to produce one item is assumes to follow a general distribution. An (s, S) policy is considered in which production stops at the instant the stock on hand reachs S and the setup of the production facility begins at an inspection point when the stock on hand drops to or below s for the first time. The time interval between two successive inspection points during a non-production period is a random variable which follows a general distribution.

• Management Science and Financial Engineering
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• v.22 no.1
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• pp.21-26
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• 2016

We analyze how firms' global production activities affect their inventory supply and financial performance in regards to its production location. For the analysis, we use information on global production quantities of 3,076 Korean multinational firms that operate business in Europe and Asia through foreign direct investment (FDI) from 2006 to 2013. Our estimation results show that an increase in global production ratio, measured by global production/total production, decreases inventory supply and financial performance of firms that produce in European countries, while it decreases financial performance of firms that produce in Asian countries. Although our results indicate that global production decreases financial performance of firms that produce in Europe and Asia, we find that its negative effects on financial performance are different based on the market demand uncertainty.

• Management Science and Financial Engineering
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• v.15 no.1
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• pp.33-49
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• 2009

We examine the effectiveness of the conventional (Q, r) model in managing production-inventory systems with finite capacity, stochastic demand, and stochastic order processing times. We show that, for systems with finite production capacity, order replenishment lead times are highly sensitive to loading and order quantity. Consequently, the choice of optimal order quantity and optimal reorder point can vary significantly from those obtained under the usual assumption of a load-independent lead time. More importantly, we show that for a given (Q, r) policy the conventional model can grossly under or over-estimate the actual cost of the policy. In cases where a setup time is associated with placing a production order, we show that the optimal (Q, r) policy derived from the conventional model can, in fact, be infeasible.

• IE interfaces
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• v.16 no.1
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• pp.111-116
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• 2003

Business integration has been considered as one of the most critical success factors that enable the firms to gain competitive edges. Despite this trend, it has also been found among not a few companies that the activities that should be functionally tied with are performed even independently. In this study, an integrated model of production planning and inventory has been developed. Computerization of the production planning activities is proposed and implemented. We also proposed the reasonable inventory levels of each item using historic data of the items, which are composed of safety stock from the given fill-rate, operating stock from the production patterns, and reserved stock from the production planning. This study has helped the firm to have clearer job definition of the related processes, to tightly control the inventory by setting and tracing the reasonable fill rates for every product, and to quickly respond to the market changes through the computerized production planning process.

• Proceedings of the Safety Management and Science Conference
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• 2004.05a
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• pp.191-201
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• 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 Safety Management & Science
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• v.6 no.3
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• pp.141-152
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• 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.