Preprint Article Version 1 This version is not peer-reviewed

Exploring the Future Development of Research, Technology and Business of Machine Tool Domain in New-Generation Information Technology Environment Based on Machine Learning

Version 1 : Received: 15 May 2019 / Approved: 16 May 2019 / Online: 16 May 2019 (10:20:58 CEST)

A peer-reviewed article of this Preprint also exists.

Chen, J.; Zhang, K.; Zhou, Y.; Liu, Y.; Li, L.; Chen, Z.; Yin, L. Exploring the Development of Research, Technology and Business of Machine Tool Domain in New-Generation Information Technology Environment Based on Machine Learning. Sustainability 2019, 11, 3316. Chen, J.; Zhang, K.; Zhou, Y.; Liu, Y.; Li, L.; Chen, Z.; Yin, L. Exploring the Development of Research, Technology and Business of Machine Tool Domain in New-Generation Information Technology Environment Based on Machine Learning. Sustainability 2019, 11, 3316.

Journal reference: Sustainability 2019, 11, 3316
DOI: 10.3390/su11123316

Abstract

The combination of new-generation information technology and manufacturing technology has resulted in major and profound impact on future development paradigm of manufacturing. It is challenging for existing methods to conduct a multidimensional trend exploration related to machine tool domain, which is the basis of virtually everything in manufacturing. In this paper, we proposed an integrating approach framework combined topic models, bibliometric, trend analysis and patent analysis to mine insightful information about future development from multi-source data related to machine tool, such as papers, grants, patents and news. Specifically, papers and grants provided two different perspectives to explore the current focuses and future trends in machine tool research. Furthermore, the future technology development of machine tool was investigated through patents analysis. Finally, news related to machine tool industry in recent years was analyzed to analyze future machine tool business mode. The integration of the above various analytical methods and the multi-dimensional mining of literatures enabled the analysis of the future development of machine tool domain systematically from multi-perspectives which include research, technology development and industry. The conclusions obtained in this paper is beneficial to different communities of machine tool in terms of determining the research directions for researchers, identifying industry opportunities for corporations and developing reasonable industry policy for policy makers.

Subject Areas

future development analysis; machine tool; machine learning; multi-source data; topic model

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