A new intelligent and data-driven product quality control system of industrial valve manufacturing process in CPS

The development of intelligent and data-driven product quality control system are emerging as key engineering technologies for industrial manufacturing process. And many studies have been made to investigate the application of quality control of industrial valve manufacturing process in cyber–physical systems (CPS). The purpose of this article is to provide a quality control and management system by using the modern electronics technology, information technology and network technology. Firstly, we propose an intelligent and data-driven framework model of product quality based on the advanced technology of digital twin (DT) and simulation methods for CPS. Secondly, we emphasize the manufacturing enterprise should hold a data accumulation, and give some useful advises on how to carry out a successful quality analysis system of industrial valve manufacturing process in CPS. Then, as a case, the intelligent method of BP neural network is constructed according to lots of quality characteristics (QCs) of the mechanical and electrical product of industrial valve, and the BP network is trained by using many quality failures of manufacturing process. Finally, the results show that the new quality control system has good accuracy and practicability by the practical example.