텍스트 마이닝을 통한 스마트 팩토리에 대한 학술적 인식 분석: 중국 학술 채널을 중심으로
Analyzing Academic Perceptions of Smart Factories Through Text Mining: A Focus on Chinese Academic Channels
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초록
제4차 산업혁명 시대에 스마트 팩토리는 제조업의 핵심 주제로 떠오르고 있으며, 특히 중국에서는 이를 통해 제조업의 혁신과 성장을 이끌고 있다. 본 연구는 중국의 스마트 팩토리에 대한 학술적 이해를 텍스트 마이닝을 통해 분석하고자 하였다. 이를 위해 2013년부터 2023년까지의 중국 학술지를 대상으로 텍스트 데이터를 수집하고 분석하여 스마트 팩토리의 학술적인 연구 동향을 파악하였다. 분석 결과, 주요 키워드인 "스마트 팩토리"는 기술 요소와 제조업 측면을 강조하며, 특히 스마트 기술, 디지털화, 데이터, 인공지능 등의 기술 관련 키워드가 빈도가 높았다. 이는 기술 혁신과 제조업 변화와 밀접한 관련성을 보여준다. 또한 연결중심성 분석에서도 이러한 키워드들이 스마트 팩토리의 핵심 개념을 형성하고 있음을 확인할 수 있었다. 그러나 스마트 팩토리 발전에는 자금 투입, 기술 표준, 직원 교육, 데이터 보안 등의 도전이 존재하며, 이를 해결하기 위해 다양한 전략이 필요하다. 이러한 연구 결과는 스마트 팩토리 분야에서의 실증적 기여와 정책 수립에 도움을 줄 수 있을 것으로 기대된다.
Abstract
In the era of the Fourth Industrial Revolution, smart factories have emerged as a core topic in manufacturing, particularly in China, where they are driving significant innovation and substantial growth in the industry. This comprehensive study aimed to analyze the academic understanding and exploration of smart factories in China through advanced text mining techniques. Text data were meticulously collected from a wide range of Chinese academic journals spanning from 2013 to 2023. These data were thoroughly analyzed to understand and elucidate the scholarly research trends regarding smart factories. The in-depth analysis revealed that the key term "smart factory" predominantly emphasizes technological elements and various manufacturing aspects, with notably high frequencies of technology-related keywords such as smart technology, digitization, data, and artificial intelligence. This finding underscores the close, intrinsic relationship between technological innovation and manufacturing transformation. Additionally, centrality analysis confirmed that these technology-centric keywords constitute the core concepts and foundational elements of smart factories. However, numerous challenges such as securing funding, establishing technical standards, employee training, and ensuring data security exist in the ongoing development of smart factories. Addressing these issues requires diverse and strategic solutions. These significant research findings are expected to contribute empirically to the academic field of smart factories and provide valuable insights for policy formulation and industrial practices.
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