• International journal of advanced smart convergence
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• v.13 no.2
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• pp.265-275
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• 2024

Smart factory is a remarkable development from traditional manufacturing systems to data-based smart manufacturing systems that can connect and process data continuously, collected from machines, production equipment to production and business processes, capable of supporting workers in making decisions or performing work automatically. Smart factory is the key and center of the fourth industrial revolution, combining improvements in traditional manufacturing activities with digital technology to help factories achieve greater efficiency, contributing to increased revenue and reduce operating costs for businesses. Besides, the importance of smart factories is to make production more quality, efficient, competitive and sustainable. Businesses in Vietnam are in the process of learning and applying smart factory models. However, the number of businesses applying the pine factory model is still limited due to many barriers and difficulties. Therefore, in this paper we conduct a survey to assess the needs and current situation of businesses in applying smart factories and propose some specific solutions to develop and promote application of smart factory model in Vietnamese businesses.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.127-140
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• 2022

With the recent development of the ICT (information and communication technology), the revolution of the industry has moved on from the third industry to the fourth. There is no doubt that the companies would not survive in the future without adopting these technologies. The purpose of this research is to analyze the intellectual structure of the internet of things(IoT) literature for the Industry 4.0 to suggest a better insight for the field. The data for this research is extracted from the Web of Science database. Total of 1,631 documents and 72,754 references are used for the research with the analysis program CiteSpace. Author co-citation analysis is used to analyze the intellectual structure and performed clustering, timeline and burst detection analysis. We identified 12 sub-areas of IoT for the Industry 4.0 which are 'Supply Chain', 'Digital Twin', 'Smart Manufacturing System' and etc. Through the timeline analysis we can find out which clusters will increase or decrease its reputation. As concluding remarks, limitations and further research suggestions are discussed.

• Asian-Australasian Journal of Animal Sciences
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• v.23 no.9
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• pp.1229-1235
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• 2010

With the increase of human activities since the Industrial Revolution, atmospheric greenhouse gas (GHG) concentration has increased, which is believed the cause of climate change. Methane ($CH_4$) fluxes were measured at two commercial swine barns (Jarvis and Guelph) with a four tower micrometeorological mass balance method. Two and three separate measurements were conducted at Jarvis and at Guelph, respectively. In the Jarvis experiments from May to July, mean $CH_4$ flux ($490.4{\mu}g/m^2/s$) during daytime was lower than that during nighttime ($678.0{\mu}g/m^2/s$) (p<0.05), which would be caused by break of slurry temperature stratification. In the Guelph experiment from January to April, mean $CH_4$ flux ($62.9{\mu}g/m^2/s$) during daytime was higher than that during nighttime ($39.0{\mu}g/m^2/s$) (p<0.05), which would be generated by high slurry temperature at 3 cm depth after April 6. Slurry temperature stratification in the Guelph experiment would happen from January to March.

• Journal of Korean Philosophical Society
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• v.146
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• pp.115-135
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• 2018

This article attempts to deal with the problem that science and technology function as a mechanism to oppress and exploit humans rather than to release humans from labor. To explore this subject, it is necessary to consider the difference between the theory of labor value and the theory of 'technology value'. In addition, it is also important to refer to Marx's critical view of the 'capitalist' use of technology. Above all, Marx' concepts of relative surplus value and special surplus value, and his analysis of organic composition of capital are still valid in explaining that development of technology tightens control over workers and intensity of labor, and worsens instability of employment. Reflection of the limitations of capitalist development of technology is also important for realization of its usefulness. Industry 4.0 in Germany therefore deserves to be noticed as a good example because it shows a different way from extreme capitalist exploitation. The model suggests also some points that shouldn't be overlooked, when we try to actualize the tremendous slogan of the current fourth industrial revolution as real innovation and progress in human life. In this matter, the most important point is the possibility of technological development that doesn't oppose workers' interests.

• Journal of Fashion Business
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• v.26 no.1
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• pp.1-15
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• 2022

Digital transformation has induced changes in human life patterns; consumption patterns are also changing to digitalization. Entering the era of industry 4.0 with the 4th industrial revolution, it is important to pay attention to a new paradigm in the fashion industry, the shift from developer-centered to user-centered in the era of the 3rd industrial revolution. The meaning of storing users' changing life and consumption patterns and analyzing stored big data are linked to consumer sentiment. It is more valuable to read emotions, then develop and distribute products based on them, rather than developer-centered processes that previously started in the fashion market. An AI(Artificial Intelligence) deep learning algorithm that analyzes user emotion big data from user experience(UX) to emotion and uses the analyzed data as a source has become possible. By combining AI technology, the fashion industry can develop various new products and technologies that meet the functional and emotional aspects required by consumers and expect a sustainable user experience structure. This study analyzes clear and useful user experience in the fashion industry to derive the characteristics of AI algorithms that combine emotions and technologies reflecting users' needs and proposes methods that can be used in the fashion industry. The purpose of the study is to utilize information analysis using big data and AI algorithms so that structures that can interact with users and developers can lead to a sustainable ecosystem. Ultimately, it is meaningful to identify the direction of the optimized fashion industry through user experienced emotional fashion technology algorithms.

• 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.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.6
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• pp.726-734
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• 2019

The current maritime industry is expected to have a significant impact on the role of maritime-related technologies and systems, especially seafarers, in the rapidly changing Fourth Industrial Revolution. The Maritime Autonomous Surface Ship (MASS) aims to reduce the number of safety accidents and improve seafarers' working environment. With regard to MASS, the International Maritime Organization has been trying to minimize unexpected impact in the maritime education and training sector by establishing international conventions such as the Standards of Training, Certification and Watchkeeping for Seafarers. However, domestic designated educational institutions have not yet established an education and training scheme to develop seafarers who will be on board for MASS. Therefore, this paper reviews the technology of MASS, analyzes the changes in education and training in order to upgrade the qualifications, and suggests the competencies of smart seafarers equipped with the integrated management ability required for Artificial Intelligence, Big Data, Cybersecurity, and the Digital System Revolution through education and training. In addition, this study provides basic information for the education and training of seafarers who are optimized for the rapidly changing technological environment.

• Korean journal of aerospace and environmental medicine
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• v.31 no.2
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• pp.33-37
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• 2021

In the era of the 4th industrial revolution, the aviation industry is also growing remarkably with the development of artificial intelligence and networks, so it is necessary to study a new concept of crew resource management (CRM), which is required in the process of operating state-of-the-art equipment. The automation system, which has been treated only as a tool, is changing its role as a decision-making agent with the development of artificial intelligence, and it is necessary to set clear standards for the role and responsibility in the safety-critical field. We present a new perspective on the automation system in the CRM program through the understanding of the autonomous system. In the future, autonomous system will develop as an agent for human pilots to cooperate, and accordingly, changes in role division and reorganization of regulations are required.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.33 no.4
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• pp.412-418
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• 2023

As advances in artificial intelligence (AI) increasingly approach areas once relegated to the realm of science fiction, there is growing public interest in using these technologies for practical everyday tasks in both the home and the workplace. This paper explores the applications of and implications for of using ChatGPT, a conversational AI model based on GPT-3.5 and GPT-4.0, in the field of occupational health and safety. After gaining over one million users within five days of its launch, ChatGPT has shown promise in addressing issues ranging from emergency response to chemical exposure to recommending personal protective equipment. However, despite its potential usefulness, the integration of AI into scientific work and professional settings raises several concerns. These concerns include the ethical dimensions of recognizing AI as a co-author in academic publications, the limitations and biases inherent in the data used to train these models, legal responsibilities in professional contexts, and potential shifts in employment following technological advances. This paper aims to provide a comprehensive overview of these issues and to contribute to the ongoing dialogue on the responsible use of AI in occupational health and safety.

• Journal of Service Research and Studies
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• v.10 no.4
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• pp.21-41
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• 2020

As the 4th Industrial Revolution unfolds rapidly, it is important to re-light the intrinsic mission given to universities from a system theory perspective as a condition for the university to survive. In this study, the university was prescribed as a fifth service industry that creates high value-added through higher education services, and attempted to provide a new and novel perspective to various university officials for the scientific rationalization of university management by re-describing it based on the Multidisciplinary perspective based on business administration, but in particular on the theory of service operation management. To this end, the primary purpose of this study is to classify the nature of educational organizations, research organizations, service organizations, and support organizations to properly perform the university's essential mission of education, research, and service, and to explore concepts and techniques for performing management activities that are appropriate to them. In addition, after identifying the university from an academic and practical point of view as a fifth service industry that creates high value-added through higher education services, but more specifically, to provide a new perspective and means for the scientific rationalization of university management by re-identifying university administration based on the business administration theory, in particular the theory of service operation management, and further reflecting a recent trend to view the university president from the CEO's point of view, the specific purpose of this study is to look at this academic system. Through this, we sought the ideal form of a systematic and scientific university management organization that can respond to new environmental changes.