• Journal of information and communication convergence engineering
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• v.17 no.3
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• pp.198-204
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• 2019

In this study, the author introduces a supply-chain management (SCM) solution that connects suppliers, manufacturers, customers, and other companies within a transactional relationship to enable efficient inventory management and timely product supply, which ultimately maximizes corporate profits. This proposed solution exploits Fourth Industrial Revolution technologies, such as artificial intelligence (AI) and the Internet of Things (IoT), which provide solutions to complex management issues generated by the broader market. The goal of the current study was to develop an advanced and intelligent smart SCM solution that complies with logistics standards, to enhance the visibility, safety, and efficiency of a supply chain made up of manufacturers and suppliers. This smart SCM solution aims at maximizing corporate profits through efficient inventory management and timely supply of products, and solves the complex management problems caused by operating within a wide range of markets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.1 no.1
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• pp.33-51
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• 2007

There are two newly emerging research issues in the enterprise information systems literature. One is the scalability issue for rapidly increasing choreographic volumes between interrelated organizations. The other is the business intelligence issue for traceable and monitorable business processes and services interchanging e-Business data and applications across organizations. Based upon these emerging issues, through a functional extension of the ebXML technology we have developed a process-driven e- Business service integration (BSI) system, which is named ‘e-Lollapalooza’. It consists of three major components ? the Choreography Modeler coping with the processdriven collaboration issue, the Runtime & Monitoring Client for coping with the business intelligence issue and the EJB-based BSI Engine coping with the scalability issue. This paper particularly focuses on the e-Lollapalooza’s development aspects for supporting the ebXML-based choreography and orchestration among the engaged organizations in a process-driven multiparty collaboration for e-Logistics and e- Commerce services. Here, it is fully deployed in an EJB-based middleware computing environment for e-Logistics process automation and B2B choreography.

• Journal of the Korea Safety Management & Science
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• v.17 no.4
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• pp.275-286
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• 2015

Global interests in RFID are increased and Korean government and companies make an active effort to propagate and spread RFID. Due to the overwhelming advantages of RFID system in comparison with existing bar code system, ripple effects on logistics sector among the utilizing fields of RFID technology are expected to be great, but application of RFID system is lowly progressed unlike the expectation of several experts. Therefore, this research extracts precedent studies on theoretical background, applying fields, promotion condition and domestic/foreign parts of RFID system, factors for operating domestic RFID system and effects and considers the effects of RFID's external variables on easiness and effectiveness of TAM. It confirms the relations of RFID applying effects for companies applying and utilizing RFID and verifies the relations among the effects for application of RFID system, accepting intention of RFID system and applying effects. Based on the results of analysis, it should play a role of good guide for all of companies and institution who will introduce RFID system to all of Korean logistics fields, make policies and systems which promote RFID acceptance nationally and socially and play a role of guide making confident climate for RFID technolog

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.168-175
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• 2023

In the era of the 4th Industrial Revolution, Logistic 4.0 using data-based technologies such as IoT, Bigdata, and AI is a keystone to logistics intelligence. In particular, the AI technology such as prognostics and health management for the maintenance of logistics facilities is being in the spotlight. In order to ensure the reliability of the facilities, Time-Based Maintenance (TBM) can be performed in every certain period of time, but this causes excessive maintenance costs and has limitations in preventing sudden failures and accidents. On the other hand, the predictive maintenance using AI fault diagnosis model can do not only overcome the limitation of TBM by automatically detecting abnormalities in logistics facilities, but also offer more advantages by predicting future failures and allowing proactive measures to ensure stable and reliable system management. In order to train and predict with AI machine learning model, data needs to be collected, processed, and analyzed. In this study, we have develop a system that utilizes an AI detection model that can detect abnormalities of logistics rotational equipment and diagnose their fault types. In the discussion, we will explain the entire experimental processes : experimental design, data collection procedure, signal processing methods, feature analysis methods, and the model development.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2399-2416
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• 2024

The current automotive industry is transitioning from Internal Combustion Engine (ICE) vehicles to Electric Vehicles (EVs), adopting a mixed assembly production approach to respond to fluctuating demand. While mixed assembly production offers the advantages of lower investment costs and flexibility in responding to changing demands, the supply of EV components requires more extensive provisioning compared to ICE vehicle components, potentially leading to unexpected issues such as congestion of transport vehicles. This study proposes a digital twin system architecture that uses Discrete Event Simulation (DES) and Business Intelligence (BI) tools to specifically address logistics challenges. The proposed architecture facilitates real-time, data-driven decision making across three layers; Data source, Simulation, and BI. It was implemented in factories engaged in the mixed assembly production of ICE and EV vehicles. The simulation challenges involve a tier 1 vendor supplying parts to Korean automobile manufacturers that produce both ICE and EV parts. A total of 240 scenarios were created to run the simulations. The deployment of the proposed architecture demonstrates its capability to quickly respond to diverse experimental situations and promptly identify potential issues.

• Journal of Digital Convergence
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• v.15 no.3
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• pp.157-163
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• 2017

Forecasting container cargo volumes is very important factor for port related organizations in inversting in the recent port management. Especially forcasting of domestic and foreign container volume is necessary because adjacent nations are competing each other to handle more container cargoes. Exact forecasting is essential elements for national port policy, however there is still some difficulty in developing the predictive model. In this respect, the purpose of this study is to develop and suggest the forecasting model of container cargo volumes of China using System Dynamics (SD). The monthly data collected from Clarkson's Shipping Intelligence Network from year 2004 to 2015 during 12 years are used in the model. The accuracy of the model was tested by comparisons between actual container cargo volumes and forecasted corgo volumes suggested by the research model. The MAPE values are calcualted as 6.21% for imported cargo volumes and 7.68% for exported cargo volumes respectively. Less than 10% of MAPE value means that the suggested model is very accurate.

• IE interfaces
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• v.20 no.2
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• pp.162-176
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• 2007

As facing the rapid advance of information technologies, the postal service is required to have capabilities of real-time logistics characterized by collaboration, ubiquity and intelligence which are necessary to the organizational management. In this study we discuss the design of the next generation information system based on real-time enterprise strategy to achieve real-time integrity and upgrade of postal information system. After briefly addressing the issues on developing information system and current situation, we provide the design direction and the framework of the to-be system. We develop detailed specification of each subsystem and provide an operational scenario. We believe when this framework is put into use, it can contribute to competitive performance by giving the integrity and consistency in implementing information systems of the Korea Postal Service.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.75-86
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• 2020

With the advent of the 4.0 era of logistics due to the Fourth Industrial Revolution, infrastructures have been built to receive the same services online and offline. Logistics services affected by logistics 4.0 and IT technology are rapidly changing. Logistics services are developing using technologies such as big data, artificial intelligence, blockchain, Internet of things, and augmented reality. The convergence of logistics services and various IT new technologies is accelerating, and the development of data management solution technology has led to the emergence of electronic cargo waybill to replace paper cargo waybill. The electronic waybill was developed to supplement paper waybill that lack economical and safety. However, the electronic waybill that appeared to complement the paper waybill are also in need of complementation in terms of efficiency and reliability. New research is needed to ensure that electronic cargo waybill gain the trust of users and are actively utilized. To solve this problem, electronic cargo waybill that combine blockchain technology are being developed. This study aims to improve the reliability, operational efficiency and safety of blockchain electronic cargo waybill. The purpose of this study is to analyze the blockchain-based electronic cargo waybill system and to derive evaluation indicators for system supplementation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.3
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• pp.181-190
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• 2024

The era of logistics 4.0 in which new technologies are applied to existing traditional logistics management has approached. It is developing based on the convergence between various technologies, and R&D are being conducted worldwide to build smart logistics by synchronizing various services with the logistics industry. Therefore, this study proposes a methodology and technology strategy that can achieve trend analysis using patent analysis and promote the development of the domestic smart logistics industry based on this. Based on the preceding research, eight key technology fields related to smart logistics were selected, and technology trends were derived through LDA techniques. After that, for the development of the domestic logistics industry, the strategy of the domestic smart logistics industry was derived based on analysis including technology capabilities. It proposed a growth plan in the field of big data and IoT in terms of artificial intelligence, autonomous vehicles, and marketability. This study confirmed smart logistics technologies by using LDA and quantitative indicators expressing the market and technology of patents in literature analysis-oriented research that mainly focused on trend analysis. It is expected that this method can also be applied to emerging logistics technologies in the future.

• IE interfaces
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• v.16 no.2
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• pp.201-210
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• 2003

The purpose of this research is to develop a scheduling system for CAL (Continuous Annealing Line) in Cold Rolling Mill. Based on CSP (Constraint Satisfaction Problem) technique in artificial intelligence, appropriate algorithms to provide schedules satisfying all the constraints imposed on CAL are designed and developed. Performance tests show that the proposed scheduling system outperforms human operators in case of aggregating the same attributes and minimizing the thickness differences between two adjacent coils.