统计与数据科学学院知识库

现如今经济增长更侧重提高质量、降低污染、增加效率，装备制造业是制造业的核心，智能制造为装备制造业的转型升级和竞争力的提升提供了新方向。装备制造业行业门类繁多，各子行业的发展规律和融合方式不同，如何准确的进行把握，分步骤、分行业推进装备制造业转型升级是新发展阶段装备制造业智能制造需要关注的重点。

基于此，本文以装备制造业为研究对象，首先梳理已有文献分析研究现状，阐述装备制造业智能制造的发展内涵、相关理论和发展现状。其次分析指标选择的理论逻辑，从基础条件、行业效益、建设水平三个维度出发构建装备制造业智能制造发展评价指标体系，综合选用纵横向拉开档次法和熵权法，选取2015~2020年中国装备制造业的相关数据，探究装备制造业八个子行业的智能制造综合发展水平以及不同维度下各子行业的发展情况。最后以测算所得的装备制造业智能制造综合发展水平为被解释变量，以人才建设、技术创新、劳动力供给、政府支持和外商投资为解释变量，选取2015~2020年装备制造业8个子行业所构建的面板数据进行实证分析，探究五个影响因素对智能制造发展的作用，对行业按规模分类后进行行业异质性分析。结论表明：装备制造业八个子行业2015~2020年智能制造综合发展水平不同步存在差异，变化趋势也不尽相同，在智能制造的基础条件、行业效益和建设水平三个维度都存在发展不协调的情况。人才建设、技术创新、劳动力供给对装备制造业智能制造发展呈显著的正向作用，政府支持对装备制造业智能制造发展呈显著的负向作用，外商投资对智能制造发展没有显著影响，三个不同规模行业智能制造发展的影响因素也不同。由此对装备制造业智能制造后续发展提出针对性的对策和建议。

Nowadays, economic growth focuses more on improving quality, reducing pollution and increasing efficiency. Equipment manufacturing industry is the core of the manufacturing industry. Intelligent manufacturing provides a new direction for the transformation and upgrading of equipment manufacturing industry and the improvement of competitiveness. There are various categories of equipment manufacturing industry, the development rules and integration ways of each sub-industry are different. How to accurately grasp, step by step, sub-industry to promote the transformation and upgrading of the equipment manufacturing industry is the new development stage of the equipment manufacturing industry intelligent manufacturing needs to focus on the key.

Based on this, this paper takes the equipment manufacturing industry as the research object. Firstly, reviews the existing literature and analyzes the research status, expounds the development connotation, related theories and development status of intelligent manufacturing in the equipment manufacturing industry. Secondly, the theoretical logic of index selection is analyzed, and the evaluation index system of intelligent manufacturing development in the equipment manufacturing industry is constructed from three dimensions: basic conditions, industrial benefits and construction level. To select the relevant data of China's equipment manufacturing industry from 2015 to 2020, the vertical and horizontal scatter degree method and entropy weight method are comprehensively used to explore the comprehensive development level of intelligent manufacturing in eight sub-industries of equipment manufacturing industry and the development situation of each sub-industry in different dimensions. Finally, the comprehensive development level of intelligent manufacturing in the equipment manufacturing industry is taken as the explained variable and talent construction, technological innovation, labor supply, government support and foreign investment are taken as the explanatory variable. The panel data constructed by eight sub-industries of the equipment manufacturing industry from 2015 to 2020 are selected for empirical analysis to explore the role of five influencing factors on the development of intelligent manufacturing. The industry is classified according to its size and then the industry heterogeneity is analyzed. The conclusion shows that the comprehensive development level of intelligent manufacturing in the eight sub-industries of equipment manufacturing industry from 2015 to 2020 is different, and the change trend is not the same. There are uncoordinated development in the three dimensions of basic conditions, industry benefits and construction level of intelligent manufacturing. Talent construction, technological innovation and labor supply have a significant positive effect on the development of intelligent manufacturing in equipment manufacturing industry, government support has a significant negative effect on the development of intelligent manufacturing in the equipment manufacturing industry, foreign investment has no significant impact on the development of intelligent manufacturing, the three industries with different sizes of intelligent manufacturing development factors are different. Therefore, targeted countermeasures and suggestions are put forward for the subsequent development of intelligent manufacturing in equipment manufacturing industry.