• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.15-31
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• 2023

In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.1
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• pp.87-109
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• 2020

Supply chain management can be defined as an information system that connects the inside and outside of a company. Its purpose is to systematically and strategically manage the flow of information, resources and services to improve the long-term performance of the entire organization, including individual companies connected to the supply chain, and the quality of service provided to customers. The ultimate goal of SCM is to create synergy through organic integration of supply and demand based on cooperation and collaboration with stakeholders in the supply chain. This study is based on the hypothesis that the company's management performance will improve as the level of SCM improves. Most of the previous studies dealt with the relationship between corporate performance and SCM in the IT area. In this study, research was conducted through human capacity with IT system. The causal relationship was demonstrated, and there was a difference in the perception of the results of this study depending on whether or not smart factories were consulted in the era of the 4th Industrial Revolution. There is a need to examine the links between management's value chain and its causal relationship.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2993-3010
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• 2021

The job shop scheduling problem (JSSP) plays a critical role in smart manufacturing, an effective JSSP scheduler could save time cost and increase productivity. Conventional methods are very time-consumption and cannot deal with complicated JSSP instances as it uses one optimal algorithm to solve JSSP. This paper proposes an effective scheduler based on deep learning technology named self-supervised long-short term memory (SS-LSTM) to handle complex JSSP accurately. First, using the optimal method to generate sufficient training samples in small-scale JSSP. SS-LSTM is then applied to extract rich feature representations from generated training samples and decide the next action. In the proposed SS-LSTM, two channels are employed to reflect the full production statues. Specifically, the detailed-level channel records 18 detailed product information while the system-level channel reflects the type of whole system states identified by the k-means algorithm. Moreover, adopting a self-supervised mechanism with LSTM autoencoder to keep high feature extraction capacity simultaneously ensuring the reliable feature representative ability. The authors implemented, trained, and compared the proposed method with the other leading learning-based methods on some complicated JSSP instances. The experimental results have confirmed the effectiveness and priority of the proposed method for solving complex JSSP instances in terms of make-span.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.400-403
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• 2021

As IoT technology becomes popular, more and more data is being generated, and the diversity of data is also increasing. In particular, in smart factory or Home IoT systems, data processing is very important because various data is collected and processed in real time through sensors. In this paper, we present a method for collecting, analyzing, and monitoring various data generated by sensors in IoT environment through Raspberry Pi. We also validate its usefulness by demonstrating that the above processed data can be operated in conjunction with smart mirror and mobile application.

• Journal of the Korean Society of Industry Convergence
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• v.23 no.2_2
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• pp.323-332
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• 2020

Container ships are getting bigger due to the increase in global cargo volume. Therefore, it needs to increase the speed for loading and unloading of containers at the quayside. Traditionally, only one container is handled at once at the quayside due to it's heavy weight. In this paper, a method of handling multiple containers at once using chassis is proposed. Proposed system is consists of a container chassis that can hold three layer stacked containers, transport system that can handle the container chassis including rail-based or vehicle-based roll-on roll-off systems, and dedicated crane system. The conceptual design of crane and transport system that can handle three stacked containers is carried out and verified. The proposed system can be adopted for real quayside container handling system with high speed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.491-494
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• 2011

We propose a green computing which similar to green chemistry; reduce the use of hazardous materials, maximize energy efficiency during the product' s lifetime, and promote the recyclability or biodegradability of defunct products and factory waste. Research continues into key areas such as making the use of computers as energy-efficient as possible, and designing algorithms and systems for efficiency-related computer technologies.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.479-482
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• 2022

Recently, various artificial intelligence technologies are being applied to smart factory, finance, healthcare, and so on. When handling data requiring protection of privacy, distributed learning techniques are used. For distribution of information with privacy protection, encoding private information is required. Minimal codes has been used in such a secret-sharing scheme. In this paper, we explain the relationship between the characteristics of the minimal codes for application in distributed systems. We briefly deals with previously known construction methods, and presents extension methods for minimal codes. The new codes provide flexibility in distribution of private information. Furthermore, we discuss application scenarios for the extended codes.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.377-389
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• 2021

This paper presents a framework design of a digital twin system for a vertical smart farm. In this paper, a framework of digital twin systems establishes three factors: 1) Client 2) IoT gateway, and 3) Server. Especially, IoT gateway was developed using the Eclipse Ditto, which has been commonly used as the standard open hardware platform for digital twin. In particular, each factor is communicating with the client, IoT gateway, and server by defining the message sequence such as initialization and data transmission. In this paper, we describe the digital twin technology trend and major platform. The proposed design has been tested in a testbed of the lab-scale vertical smart-farm. The sensor data is received from 1 Jan to 31 Dec 2020. In this paper, a prototype digital twin system that collects environment and control data through a raspberry pi in a plant factory and visualizes it in a virtual environment was developed.

• Journal of the Korea Society of Computer and Information
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• v.27 no.7
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• pp.65-73
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• 2022

Recently, as the Windows system supports the Windows subsystem for Linux (WSL), various researchers have studied to apply a docker container on various systems such as server systems, workstation system and so on. However, in various existing researchers, there is a lack of performance-related indicators to apply the system to each operating system (linux system and windows system). In this paper, we compared a performance comparison and analysis of container-based host operating systems. We configured experimental environments of operating systems for microsoft windows systems and linux systems based on a docker container support. In experimental results, the containers of linux systems reduced the average data latency of dataset 1-6 by 3.9%, 62.16%, 1552.38%, 7.27%, 60.83%, and 1567.2%, compared to the containers on microsoft windows systems.

• Journal of Korea Multimedia Society
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• v.22 no.3
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• pp.366-373
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• 2019

The development of monitoring and analysis systems to increase productivity while saving energy is needed as a method to reduce huge amount of energy consumed in the process of producing large forged products. In this paper, we propose a system to monitor and analyze energy usage in real-time collected from gas-meter, wattmeter, and thermometer based on IoT installed in forging factories. The system consists of a data collection server for collecting and processing data from IoT- based platform and existing SCADA equipment and ERP/MES system in forging factories, and an application server for providing services to users. To develop the system, the overall system structure is logically diagrammed, and the databases configuration and implementation modules to efficiently store and manage data are presented. In the future, the system will be utilized to reduce energy consumption by analyzing energy usage pattern and optimizing process works with real-time energy usage and production process data for each facility.