Information and communication technology is undergoing rapid development, and many disruptive technologies, such as cloud computing, Internet of Things, big data, and artificial intelligence, have emerged. These techn...Information and communication technology is undergoing rapid development, and many disruptive technologies, such as cloud computing, Internet of Things, big data, and artificial intelligence, have emerged. These technologies are permeating the manufacturing industry and enable the fusion of physical and virtual worlds through cyber-physical systems （CPS）, which mark the advent of the fourth stage of industrial production （i.e., Industry 4.0）. The widespread application of CPS in manufacturing environments renders manufacturing sys- tems increasingly smart. To advance research on the implementation of Industry 4.0, this study examines smart manufacturing systems for Industry 4.0. First, a conceptual framework of smart manufacturing systems for Industry 4.0 is presented. Second, demonstrative scenarios that pertain to smart design, smart machining, smart control, smart monitoring, and smart scheduling, are presented. Key technologies and their possible applications to Industry 4.0 smart manufacturing systems are reviewed based on these demonstrative scenarios. Finally, challenges and future perspectives are identified and discussed.展开更多
本文在国民经济核算体系(System of National Accounts,SNA)框架下估算中国制造业分行业研发(R&D)资本存量,为后续经济分析提供相对可靠的基础数据。首先,利用辅助指标和统计检验对R&D支出及其构成进行估算与调整,有效解决行业...本文在国民经济核算体系(System of National Accounts,SNA)框架下估算中国制造业分行业研发(R&D)资本存量,为后续经济分析提供相对可靠的基础数据。首先,利用辅助指标和统计检验对R&D支出及其构成进行估算与调整,有效解决行业分类和统计口径等数据不可比问题;其次,在SNA-2008框架下将R&D支出转换为R&D投资,利用BEA方法估算得到1990-2016年制造业28个两位数行业的R&D资本存量;最后,对典型行业进行深入比较分析,提出有针对性的政策建议。结果显示:(1)制造业R&D资本存量总体上呈现快速增长趋势;(2)以计算机、通信和其他电子设备制造业为代表的高技术产业是科技创新的主要力量,但在基础研究领域没有明显优势且对传统制造业的引领作用尚显不足;(3)传统制造业对科技创新的贡献相对减少但地位仍然重要,部分传统制造业已经成为R&D资本存量新的增长点。展开更多
文摘Information and communication technology is undergoing rapid development, and many disruptive technologies, such as cloud computing, Internet of Things, big data, and artificial intelligence, have emerged. These technologies are permeating the manufacturing industry and enable the fusion of physical and virtual worlds through cyber-physical systems （CPS）, which mark the advent of the fourth stage of industrial production （i.e., Industry 4.0）. The widespread application of CPS in manufacturing environments renders manufacturing sys- tems increasingly smart. To advance research on the implementation of Industry 4.0, this study examines smart manufacturing systems for Industry 4.0. First, a conceptual framework of smart manufacturing systems for Industry 4.0 is presented. Second, demonstrative scenarios that pertain to smart design, smart machining, smart control, smart monitoring, and smart scheduling, are presented. Key technologies and their possible applications to Industry 4.0 smart manufacturing systems are reviewed based on these demonstrative scenarios. Finally, challenges and future perspectives are identified and discussed.
文摘本文在国民经济核算体系(System of National Accounts,SNA)框架下估算中国制造业分行业研发(R&D)资本存量,为后续经济分析提供相对可靠的基础数据。首先,利用辅助指标和统计检验对R&D支出及其构成进行估算与调整,有效解决行业分类和统计口径等数据不可比问题;其次,在SNA-2008框架下将R&D支出转换为R&D投资,利用BEA方法估算得到1990-2016年制造业28个两位数行业的R&D资本存量;最后,对典型行业进行深入比较分析,提出有针对性的政策建议。结果显示:(1)制造业R&D资本存量总体上呈现快速增长趋势;(2)以计算机、通信和其他电子设备制造业为代表的高技术产业是科技创新的主要力量,但在基础研究领域没有明显优势且对传统制造业的引领作用尚显不足;(3)传统制造业对科技创新的贡献相对减少但地位仍然重要,部分传统制造业已经成为R&D资本存量新的增长点。
