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The technological advancements promote the rise of the fourth industrial revolution, where key terms are efficiency, innovation, and enterprises' digitalization. Market globalization, product mass customization, and more complex products need to reflect on changing the actual design methods and developing business processes and methodologies that have to be data-driven, AI-assisted, smart, and service-oriented. Therefore, there is a great interest in experimenting with emerging technologies and evaluating how they impact the actual business processes. This paper reports a comparison among the major trends in the digitalization of a Factory of the Future, in conjunction with the two major strategic programs of Industry 4.0 and China 2025. We have focused on these two programs because we have had experience with them in the context of the FIRST H2020 project. European industrialists identify the radical change in the traditional manufacturing production process as the rise of Industry 4.0. Conversely, China mainland launched its strategic plan in China 2025 to promote smart manufacturing to digitalize traditional manufacturing processes. The main contribution of this review paper is to report about a study, conducted and part of the aforementioned FIRST project, which aimed to investigate major trends in applying for both programs in terms of technologies and their applications for the factory's digitalization. In particular, our analysis consists of the comparison between Digital Factory, Virtual Factory, Smart Manufacturing, and Cloud Manufacturing. We analyzed their essential characteristics, the operational boundaries, the employed technologies, and the interoperability offered at each factory level for each paradigm. Based on this analysis, we report the building blocks in terms of essential technologies required to develop the next generation of a factory of the future, as well as some of the interoperability challenges at a different scale, for enabling inter-factories communications between heterogeneous entities. [ABSTRACT FROM AUTHOR]

In this paper, multi-process collaboration subsystem, multi-intersection collaboration subsystem, and multi-operator collaboration subsystem are deduced through the overall architecture of Smart Manufacturing Collaborative System (SMCS). Furthermore, the detailed implementation steps of SMCS are given, and verified by a case study in an automotive enterprise, which can realize the sharing of information, data and resources between adjacent business links and improve the utilization rate of enterprise's overall information and data resources. It also can improve design efficiency, save manufacturing costs and improve supply response speed. Then, it can save communication costs, and improve the utilization rate of information service resources. [ABSTRACT FROM AUTHOR]

In the current trend of smart manufacturing, the architecture of smart manufacturing is gradually proposed by many countries in the world. Main components, elements, functions, and relationships of these smart manufacturing architectures have been clarified. However, the specific details of cross matching of different dimensions in these smart manufacturing architectures have not been thoroughly developed. Therefore, a certain part of a plane intersected of system hierarchy dimension and smart characteristics dimension in the model for smart manufacturing (SMS) from a perspective of implementation was selected for detailed study, which is defined as smart manufacturing implementation system (SMIS). Firstly, a top-level scenario planning of SMIS was proposed from perspectives of lean factory, interconnection factory, information factory, transparent factory, virtual factory, and smart factory. Then, an overall framework of SMIS was deduced through a top-level scenario planning of SMIS. Finally, through a case study, the specific implementation process of SMIS is obtained. Through the proposed overall framework and implementation path of SMIS, enterprises can implement intelligent manufacturing step by step. In addition, the top-level scenario planning and overall framework of SMIS are complementary to the SMS proposed by China. [ABSTRACT FROM AUTHOR]

In the tide of smart manufacturing in the world, many countries have put forward their own reference frameworks for smart manufacturing system. Based on the framework of smart manufacturing system (SMS) proposed by China, a reference smart manufacturing integration system (SMIS) from multi-level and multi-perspective was proposed. The reference model of SMIS was analyzed by means of system engineering. Based on this model, the overall architecture of SMIS was proposed. Then, the physics subsystem, information integration subsystem, network integration subsystem, data integration subsystem, and visualization integration subsystem for SMIS were proposed through the overall architecture of SMIS. Finally, the above integrated subsystems were collected together to deduce the implementation path of SMIS. Four reference subsystems for SMIS proposed in this paper have achieved good effects in the projects we participated in, which were organized by the state. The research results of this paper can be used as a reference for industry and government to design, set, and carry out SMIS. At the same time, it has a certain reference value for the improvement and supplement of national smart manufacturing system architecture. [ABSTRACT FROM AUTHOR]

Taking smart manufacturing as a strategy for industrial development, China has put forward a people-oriented policy and launched a series of plans for smart manufacturing talent education (SMTE). The demand for smart manufacturing talents in ten priority areas and the industrial applications in China is very huge. Therefore, in this paper, a reference system of SMTE in China is presented, which includes discipline system, training system, practice system, and assessment system. In order to further refine the architecture of smart manufacturing system, a reference course system was proposed; the system contains seven layers, which are basic layer, technique layer, implementation layer, management layer, platform layer, application layer, and industrialization layer. Finally, nine stakeholders of the common operation body were investigated, and a reference implementation of SMTE in China was put forward. In this paper, the smart manufacturing talent education reference system, reference model, and related reference subsystems can be a very useful guideline for Chinese industry and education to design, set, and carry out the smart manufacturing talent education system. At the same time, the system has its reference value for the improvement of China's smart manufacturing system architecture. [ABSTRACT FROM AUTHOR]