Abstract

With the continuous improvement of hardware product performance and data processing capability and the rapid development of network communication technology, the intelligent technology of computer systems is becoming more and more mature, and the intelligence of manufacturing has become the focus of people's attention. The intelligent performance of manufacturing is to use the knowledge obtained from data analysis to make inferences and decisions to solve problems, and the Cyber-Physical System (CPS) supports the deep integration of informationization and industrialization by integrating advanced information technology and automatic control technology, such as perception, computation, communication, control, etc. Although there has been great progress in the research of CPS, it has been widely used in the development of computer systems. Despite significant progress in CPS research, some key issues have yet to be fully addressed at the shop floor level, including dynamic reorganization and local intelligence. These issues have hindered the research on the intelligence of complex processes. For progress units of complex processes, this study proposes a CPS-based smart progress unit (SPU) construction method. In order to improve machining efficiency and quality consistency, this study proposes a multi-source data acquisition technique and a multi-objective optimization algorithm to process the data within the machining unit. Finally, this study takes the paddle boring process as an example, and designs hardware and software systems to automate the paddle boring process and meet the needs of automation and intelligent transformation of the paddle boring process.

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