• Journal of Korea Society of Industrial Information Systems
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• v.28 no.4
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• pp.77-92
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• 2023

In this study, keyword network analysis was performed based on global and domestic journals, and network text analysis was conducted for news and articles to examine major issues and research trends on supply chain risks after COVID-19. As a result of analyzing the supply chain risk, after COVID-19 which was relatively insufficient in previous studies, research trends and topics such as supply chain risk recovery, response and public welfare, which are different from previous previous studies, were found in global and domestic journals, news and articles and it was possible to suggest practical strategies and insights for supply chain risk strategies for firms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2029-2046
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• 2016

Energy consumption is an important index in mobile ad hoc networks. Data packet transmission increases among nodes, particularly in big data communication. However, nodes may be unable to transmit data packets because of energy over-consumption. Consequently, information may be lost and network communication may block. While opportunistic network is a kind of mobile ad hoc networks, researchers do not focus on energy consumption in opportunistic network communication. This study proposed an effective sensor energy supply scheme that can be applied in opportunistic networks. This scheme considers nodes sensor requests and communication model. In this scheme, nodes do not only accomplish energy supply in communication, but also extend communication time in opportunistic networks. Compared with the Spray and Wait algorithm and the Binary Spray and Wait algorithm in simulations, the proposed scheme extends communication time, increases data packet transmission, and accomplishes energy supply among nodes.

• Journal of Korean Society on Water Environment
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• v.28 no.2
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• pp.202-212
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• 2012

Due to the deterioration of water supply network and the deficiency of raw water, the water utility of local governments have performed various projects to improve their revenue water ratio. However, it is very difficult to estimate the cost for maintaining the revenue water ratio at higher level after completing the project, because local governments have different conditions affecting the operating and maintenance cost of water supply network. The purpose of this study is to present a procedure to estimate the operating and maintenance cost required to maintain the target revenue water ratio of the water supply network. For this purpose, we estimated the cost used only for operation and maintenance of water supply network of 164 local governments with the aid of K-Mean Clustering Analysis and the data from 40 representative local governments. Then, the regression analysis was performed to find relationship between revenue water ratio and the operating and maintenance cost with two different data sets generated by two classification methods; the first method classifies the local governments by means of k-means clustering, and the other classifies the local governments according to the index standardized by the operating and maintenance cost per unit length of water mains per revenue water ratio. The results shows that the method based on the index standardized by the cost and revenue water ratio of each government produces more reliable results for finding regression equations between revenue water ratio and the operating and maintenance cost only for water supply network. The estimated regression equations for each group can be used to estimate the cost required to keep the target revenue water ratio of the local government.

• Korean Management Science Review
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• v.21 no.2
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• pp.15-25
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• 2004

Great effort has been exerted to redesign the supply chain network as a means to improve corporate competitiveness. In this study, we present a mathematical model and a solution system to help redesign corporate logistics networks. The objective of the model is to minimize total logistics costs. We applied the solution system to real problem cases. We use the model and the concept to develop decision support system that is based on C++ with the use of CPLEX callable library as a solution engine. We tested and verified the DSS for redesigning the network of a large Korean electronics company. Through various scenario analyses. we recommend to redesign their supply chain network that demonstrates the possibility of substantial logistics cost savings.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.3
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• pp.9-22
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• 2021

This study proposes a supply chain network (SCN) model considering supply disruption in assembly industry. For supply disruption, supplier disruption and its route disruption are simultaneously taken into consideration in the SCN model. With the simultaneous consideration, the SCN model can achieve its flexibility and efficiency. A mathematical formulation is suggested for representing the SCN model, and a proposed hybrid genetic algorithm (pro-HGA) is used for implementing the mathematical formulation. In numerical experiment, the performance of the pro-HGA approach is compared with those of some conventional approaches using the SCN models with various scales, and a sensitivity analysis considering the change of the numbers of suppliers and backup routes is done. Experimental results show that the performances of the pro-HGA approach are superior to those of the conventional approaches, and the flexibility and efficiency of the SCN model considering supply disruption are proved. Finally, the significance of this study is summarized and a potential future research direction is mentioned in conclusion.

• Food Science of Animal Resources
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• v.33 no.4
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• pp.463-473
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• 2013

Through the development of efficient data collecting technologies like RFID, and inter-enterprise collaboration platforms such as web services, companies which participate in supply chains can acquire visibility over the whole supply chain, and can make decisions to optimize the overall supply chain networks and processes, based on the extracted knowledge from historical data collected by the visibility system. Although not currently active, the MeatWatch system has been developed, and is used in part for this purpose, in the imported beef distribution network in Korea. However, the imported beef distribution network is too complicated to analyze its various aspects using ordinary process analysis approaches. In this paper, we suggest a novel approach, called RFID-based supply chain process mining, to automatically discover and analyze the overall supply chain processes from the distributed RFID event data, without any prior knowledge. The proposed approach was implemented and validated, by using a case study of the imported beef distribution network in Korea. Specifically we demonstrated that the proposed approach can be successfully applied to discover supply chain networks from the distributed event data, to simplify the supply chain networks, and to analyze anomaly of the distribution networks. Such novel process mining functionalities can reinforce the capability of traceability services like MeatWatch in the future.

• Journal of Korean Society of Water and Wastewater
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• v.27 no.1
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• pp.1-10
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• 2013

Major issues in water supply service have changed from expansion of service area to improvement of service quality, i.e., water quality and safety, and early response to emergency situation. This change in the service concept triggers the perceptions of limitation with the current centralized water supply system and of necessities of decentralized (distributed) water supply system (DWSS), which can make up the limitations. DWSS can reduce the possibility of water supply outage by establishing multiple barriers such as emergency water supply system, and secure better water quality by locating treatment facilities neighboring consumers. On the other hand, fluctuation of water demand will be increased due to the reduced supply area, which makes difficult to promptly respond the fluctuating demand. In order to supplement this, hybrid water supply system was proposed, which combined DWSS with conventional water supply system using distributing reservoir to secure the stability of water supply. The Optimal connection point of DWSS to existing water supply network in urban area was determined by simulating a supply network using EPANET. Optimal location of decentralized water treatment plant (or connection point) is a nodal point where changes in pressure at other nodal points can be minimized. At the same time, the optimal point should be selected to minimize hydraulic retention time in supply network (water age) to secure proper water quality. In order to locate the point where these two criteria are satisfied optimally, Distance measure method, one of multi-criteria decision making was employed to integrate the two results having different dimensions. This methodology can be used as an efficient decision-support criterion for the location of treatment plant in decentralized water supply system.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.65-74
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• 2020

Many of companies have made significant improvements for globalization and competitive business environment The supply chain management has received many attentions in the area of that business environment. The purpose of this study is to generate realistic production and distribution planning in the supply chain network. The planning model determines the best schedule using operation sequences and routing to deliver. To solve the problem a hybrid approach involving a genetic algorithm (GA) and computer simulation is proposed. This proposed approach is for: (1) selecting the best machine for each operation, (2) deciding the sequence of operation to product and route to deliver, and (3) minimizing the completion time for each order. This study developed mathematical model for production, distribution, production-distribution and proposed GA-Simulation solution procedure. The results of computational experiments for a simple example of the supply chain network are given and discussed to validate the proposed approach. It has been shown that the hybrid approach is powerful for complex production and distribution planning in the manufacturing supply chain network. The proposed approach can be used to generate realistic production and distribution planning considering stochastic natures in the actual supply chain and support decision making for companies.

• Korean Management Science Review
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• v.30 no.1
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• pp.25-41
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• 2013

This paper presents a supply chain framework with the ODM (Original Design Manufacturing)-OEM (Original Equipment Manufacturing) hybrid production of textile industry in FTA (Free Trade Agreements) environments between Korea and other countries. The proposed supply chain framework with ODM-OEM hybrid production is a unique supply chain that has both domestic production with non-tariff advantages in FTA environment and oversea production with low labor costs. To investigate the validity of the proposed supply chain, we first construct its strategic profit model and supply chain planning and then show that each member of supply chain network-yarn manufacturer, fabric manufacturer, and apparel manufacturer-can maximize their own profits without conflicts among the members. The efficiency of the ODM-OEM hybrid production system is analytically verified in comparison with the general OEM and ODM production model using profit models. Comprehensive numerical examples are provided to illustrate the advantages of the proposed system.

• Journal of Environmental Impact Assessment
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• v.14 no.4
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• pp.157-164
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• 2005

Existing models that predict of Daily water supply include statistical models and neural network model. The neural network model was more effective than the statistical models. Only neural network model, which predict of Daily water supply, is focused on estimation of the operational control. Neural network model takes long learning time and gets into local minimum. This study proposes Neuro Genetic hybrid model which a combination of genetic algorithm and neural network. Hybrid model makes up for neural network's shortcomings. In this study, the amount of supply, the mean temperature and the population of the area supplied with water are use for neural network's learning patterns for prediction. RMSE(Root Mean Square Error) is used for a MOE(Measure Of Effectiveness). The comparison of the two models showed that the predicting capability of Hybrid model is more effective than that of neural network model. The proposed hybrid model is able to predict of Daily water, thus it can apply real time estimation of operational control of water works and water drain pipes. Proposed models include accidental cases such as a suspension of water supply. The maximum error rate between the estimation of the model and the actual measurement was 11.81% and the average error was lower than 1.76%. The model is expected to be a real-time estimation of the operational control of water works and water/drain pipes.