Analyzing Technological Trends of Smart Factory using Topic Modeling
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초록
Recently, smart factories have gained significant importance since the development of the fourth industrial revolution and the rise of global industrial competition. Therefore, the industries' survival to meet the global market trends requires accurate technological planning. Although, different works are available to investigate forecasting technologies and their influence on the smart factory. However, little significant work is available yet on the analysis of technological trends concerning the smart factory, which is the core focus herein. This work was performed to analyze the technological trends of the smart factory, followed by a detailed investigation of recent research hotspots/frontiers in the field. A well-known topic modeling technique, namely Latent Dirichlet Allocation (LDA), was employed for this study described above. The technological trends were further strengthened with the in-depth analysis of a smart factory-based case study. The findings produced the technological trends which possess significant potential in determining the technological strategies. Moreover, the results of this work may be helpful for researchers and enterprises in forecasting and planning future technological evolution.
Abstract
Recently, smart factories have gained significant importance since the development of the fourth industrial revolution and the rise of global industrial competition. Therefore, the industries' survival to meet the global market trends requires accurate technological planning. Although, different works are available to investigate forecasting technologies and their influence on the smart factory. However, little significant work is available yet on the analysis of technological trends concerning the smart factory, which is the core focus herein. This work was performed to analyze the technological trends of the smart factory, followed by a detailed investigation of recent research hotspots/frontiers in the field. A well-known topic modeling technique, namely Latent Dirichlet Allocation (LDA), was employed for this study described above. The technological trends were further strengthened with the in-depth analysis of a smart factory-based case study. The findings produced the technological trends which possess significant potential in determining the technological strategies. Moreover, the results of this work may be helpful for researchers and enterprises in forecasting and planning future technological evolution.
참고문헌 (33)
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