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| Technology Convergence and Evolution Path Detection: Technology Group Similarity Method Based on Time Series Analysis |
| Chen Yue1, Wang Kang1, Song Chao1, Zuo Jia1, Pan Yuntao2, Gao Jiping2 |
1.Institution of Science of Science and S&T Management & WISE Lab, Dalian University of Technology, Dalian 116024
2.Institute of Scientific and Technical Information of China, Beijing 100038 |
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Abstract This paper presents the technology group similarity time series analysis method for technology fusion and evolution path detection to analyze technology development paths in the field of additive manufacturing. To this end, first, the study takes additive manufacturing technology patent data as the analysis object and measures the overall change trend of the technical field from the level of patent documentation, technical level, and technical domain level. Second, based on the co-occurrence principle of IPC classification number, the study uses the detection algorithm, identifies technology groups, and correlates the technology groups in adjacent time intervals through cosine similarity. Finally, visualization techniques are used to show the fusion and diffusion evolution relationships between the technology groups in different time intervals. The results of the study show that the additive manufacturing technology is undergoing a stage of rapid development, wherein the technology integration capability and inheritance is gradually enhanced. Additionally, this technical field has become relatively independent. The evolution path of the technology fusion and diffusion is clarified, primarily including additive manufacturing materials and processes, computer-aided design, and the three key paths of additive manufacturing applications. Recently, metal additive manufacturing and arc additive manufacturing have transformed into technical hot spots, and biomedical, construction, and food fields have become key technology application areas. The method presented in this study supplements the traditional IPC co-occurrence method. Furthermore, it shows the technological evolution path from a dynamic perspective, providing a new perspective and technical means for comprehensive detection of technological evolution path.
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Received: 30 May 2020
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