Bibliometric analysis of micro-nano manufacturing technologies

Maryna Bodnariuk , Ruslan Melentiev
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引用次数: 19

Abstract

Manufacturing is the primary industry promoting economic and social development. For the past 30 years, the global trends of preciseness and device miniaturisation have promoted manufacturing to the micro (μ) and nano (η) scale. Identification of the most promising micro-nano manufacturing technologies (MNMT) is of interest to industry, academia and private and national science investing foundations. Considering the exponential broadening of the research area and an enormous volume of literature, providing an overview of the state of the art is far beyond the scope of a technical review paper. This study performs bibliometric analysis of a stream of academic literature devoted to μ- and η-machining. The main goals of the analysis are to assess the current core and trends in the field of MNMT. Literature and citation statistics from 1988 were collected from the Web of Science, Google Scholar, Scopus, Engineering Village, ScienceDirect and SpringerLink databases and were then analysed and illustrated with Microsoft Excel and VOSviewer software. The top keywords, articles, journals, authors, universities and countries were identified according to different parameters. The index of normalised influence was offered to evaluate the top element in each category. We observed that the most powerful keywords were present in well-known articles published in prominent journals by authoritative scientists at leading universities in the countries that are most actively engaged in MNMT. The implications of the research outcomes for investors and academicians are summarised in the conclusion.

微纳制造技术的文献计量学分析
制造业是推动经济社会发展的第一产业。在过去的30 年里,精密化和器件小型化的全球趋势推动了制造向微(μ)和纳米(η)尺度发展。确定最有前途的微纳米制造技术(MNMT)是工业界、学术界、私人和国家科学投资基金会感兴趣的问题。考虑到研究领域的指数级扩展和大量的文献,提供技术状态的概述远远超出了技术评论论文的范围。本研究进行了文献计量分析的学术文献流致力于μ和η加工。分析的主要目的是评估当前MNMT领域的核心和趋势。从Web of Science、b谷歌Scholar、Scopus、Engineering Village、ScienceDirect和SpringerLink数据库中收集1988年以来的文献和引文统计数据,然后使用Microsoft Excel和VOSviewer软件进行分析和说明。排名靠前的关键词、文章、期刊、作者、大学和国家是根据不同的参数确定的。给出了归一化影响指数来评价每个类别中的顶级元素。我们观察到,最具影响力的关键词出现在最积极参与MNMT的国家的顶尖大学的权威科学家在著名期刊上发表的知名文章中。结论部分总结了研究结果对投资者和学者的启示。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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