Abstract
Digital twin (DT) can facilitate interaction between the physical and the cyber worlds and achieve smart manufacturing. However, the DT’s development in the industry remains vague. This study investigates the global patent databases of DT patents and summarizes related technologies, effects, and applications. Patent map analysis is used to uncover the patent development trajectory of DT in the patent databases of the USA, China, and the World Intellectual Property Organization among European nations. In addition, a nation-based survey is conducted to explore their DT patent trends. Findings reveal that DT fails to form a comprehensively connected technology, which is a typical phenomenon for a technology that remains in its early stage of development. In the present study, the two-dimensional matrix analysis of patent technology and effect exhibits that several patents created a variety of effects and reached saturation. Moreover, several technology–effect domains remain, and DT-related technology gaps exist in a number of potential effects. The DT-related patents are distributed unevenly in various industries. For instance, most of the DT-related patents appear in the manufacturing industry. Furthermore, our K-mode cluster analysis reveals that the DT-related patents are distributed in five subgroups of the three dimensions, namely, technology, effect, and application.
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Appendices
Appendix 1
Appendix 2. The detailed analysis of technology, effect, and application by country
1.1 A2-1. USA
The two-dimensional analysis of patent technology and effect in the USA showed that its major development of four technologies include management technology (Technology #1), wearable device technology (Technology #2), network and communication technology (Technology #3), and data analytics technology (Technology #4). It covers seven types of effects, including technology resolving manufactory operations (Effect #1), data organization and integration (Effect #2), and pattern recognition and classification (Effect #3) (refer to Fig. 7a with solid line). However, there are several patent gaps; for instance, wearable device technology (Technology #2) has not solved issues of manufacturing operations (Effect #1), pattern recognition and classification (Effect #3), disruption, diagnostic, and prevention (Effect #7). For data analytics technology (Technology #4), it has not solved issues of manufacturing operations (Effect #1). In addition, the technology and application matrix showed that the USA mainly developed patents in the manufacturing (Application #1) and general industry (Application #12) (refer to Fig. 7b with solid line).
1.2 A2-2 The World Intellectual Property Organization
Among the patents produced by the WIPO, most were management technology (Technology #1) resolve manufacturing operations (Effect #1) applications, followed by data analysis technology (Technology #4) resolve data organization and integration (Effect #2) and then computing, security, and safety technology (Technology #8) resolve disruptions, diagnostics, and prevention (Effect #7) (refer to Fig. 8a with solid line). Additionally, the technology-application realm matrix shows that the WIPO mainly developed patents in the realms of manufacturing (Application #1) and general industry (Application #12), especially general industry (refer to Fig. 8a with solid line).
1.3 A2-3. China
The patent technology and effect matrix for China (Fig. 9a) showed that currently, China has three focuses in patent technology and effect development. The first part is management technology (Technology #1), wearable device technology (Technology #2), network and communication technology (Technology #3), and data analytics technology (Technology #4), which are used to solve problems in manufacturing operations (Effect #1), data organization and integration (Effect #2), as well as pattern recognition and classification (Effect #3). The second part is management technology (Technology #1), wearable device technology (Technology #2), network and communication technology (Technology #3), and data analytics technology (Technology #4), for resolving issues of communication capability (Effect #6) as well as disruption, diagnostics, and prevention (Effect #7). The third part is sensor technology (Technology #6), optimization and machine learning system (Technology #7), and computing, security, and safety technology (Technology #8), exhibiting seven types of effects, including manufacturing operations (Effect #1) as well as data organization and integration (Effect #2) (refer to Fig. 9a with solid line). But, there are also patent gaps in the more concentrated patent blocks, including management technology (Technology #1) has not solved issues with form decision-making and support (Effect #4), and learning ability and self-organization (Effect #5), wearable device technology (Technology #2) has not solved problems with data organization and integration (Effect #2), pattern recognition and classification (Effect #3), decision-making and support (Effect #4), learning ability and self-organization (Effect #5), network and communication technology (Technology #3) has not solved issues of decision-making and support (Effect #4), data analytics technology (Technology #4) has not solved issues of learning ability and self-organization (Effect #5), optimization and machine learning system (Technology #7) has not solved issues of pattern recognition and classification (Effect #3) (refer to Fig. 9 with dashed line). On the other hand, China revealed in its patent strategies that it did not develop human–machine interfaces technology (Technology #5). Also, its technology and application field matrix shows that China is primarily focused on patent development in general industry (Application #12) (refer to Fig. 9b with solid line).
1.4 A2-4. European Nations
The patent technology and function matrix of the European Nations (EU) (Fig. 10) showed that currently, the EU has three focuses in patent technology and effect development. The first part is management technology (Technology #1), wearable device technology (Technology #2), network and communication technology (Technology #3), data analytics technology (Technology #4), and human–machine interfaces technology (Technology #5), which are used solve problems in manufacturing operations (Effect #1), data organization and integration (Effect #2), as well as pattern recognition and classification (Effect #3). The second part is management technology (Technology #1), wearable device technology (Technology #2), network and communication technology (Technology #3), data analytics technology (Technology #4), and human–machine interfaces technology (Technology #5), which solve problems in learning ability and self-organization (Effect #5), communication capability (Effect #6), as well as disruption, diagnostics, and prevention (Effect #7). The third part is optimization and machine learning system (Technology #7), and computing, security, and safety technology (Technology #8), demonstrating five effects, including manufacturing operations (Effect #1) as well as data organization and integration (Effect #2) (refer to Fig. 10 with solid line).
Nevertheless, there are also patent gaps in the more concentrated patent blocks, including management technology (Technology #1) has solved issues with form data organization and integration (Effect #2), and learning ability and self-organization (Effect #5), wearable device technology (Technology #2) has solved problems with manufacturing operations (Effect #1), pattern recognition and classification (Effect #3), communication capability (Effect #6), and disruption, diagnostic, and prevention (Effect #7), network and communication technology (Technology #3) has solved issues of data organization and integration (Effect #2), and disruption, diagnostic, and prevention (Effect #7), data analytics technology (Technology #4) has solved issues of manufacturing operations (Effect #1), and communication capability (Effect #6), human-machine interfaces technology (Technology #5) has solved issues of pattern recognition and classification (Effect #3), optimization and machine learning system (Technology #7) has solved issues of data organization and integration (Effect #2), pattern recognition and classification (Effect #3), decision-making and support (Effect #4), communication capability (Effect #6), and disruption, diagnostic, and prevention (Effect #7), computing, security and safety technology (Technology #8) has solved issues of manufacturing operations (Effect #1), pattern recognition and classification (Effect #3), decision-making and support (Effect #4), and learning ability and self-organization (Effect #5) (refer to Fig. 10 with dashed line).
The European Patent Office revealed in its patent strategies that it did not develop sensor technology (Technology #6). As for its effects, it did not consider decision support or regulation of this type of effects. Also, its technology and application field matrix (Fig. 10b) showed that the European Patent Office primarily focused on patent development in manufacturing (Application #1) and general industry (Application #12), especially general industry (refer to Fig. 10 with solid line).
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Wang, KJ., Lee, TL. & Hsu, Y. Revolution on digital twin technology—a patent research approach. Int J Adv Manuf Technol 107, 4687–4704 (2020). https://doi.org/10.1007/s00170-020-05314-w
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DOI: https://doi.org/10.1007/s00170-020-05314-w