An Intelligent Product-Driven Manufacturing System Using Data Distribution Service - Chin-Te Lin; Hong-Ji Lu (IEEE Access, 2024)
As key components of smart factories, intelligent production machines are gradually becoming a major capital asset of companies in the market, offering connectivity, interoperability, and services. However, due to commercial and technological constraints, production machines rarely provide enough information for customers to develop data-driven applications. Therefore, this research proposes that intelligence be built into them to assist in production control and allow relevant data to be collected and made available for future use. In order to realize this proposal, an operational paradigm for such systems is first outlined in this paper. Then, the states of workpieces in a production environment are classified, and the methods of generation, operation, and transfer of instances are described. The next step is to build an intelligent product-driven manufacturing system using Data Distribution Service (DDS). Intelligent workpieces and machines collaborate to complete production tasks in such a system. During this collaborative process, an intelligent workpiece continuously collects relevant data and packages it together for the customer on its transformation into a final product. The feasibility of this intelligent product-driven manufacturing system is examined by upgrading a classic manufacturing factory. In addition, the study explores the system architecture, the implementation of a classic system upgrade, the production data collection, and the intellectualization of data assets. In conclusion, the results of this study will help machine builders expand their business models, providing customers with production machines that carry data for advanced data-driven applications.