The current pipeline surface generation algorithm cannot get the angle information of the corner of complex pipeline surface, which leads to the poor accuracy of the algorithm, the slow speed of 3D point cloud intelligent mosaic, and the large number of effective points. Therefore, a CAD surface generation algorithm for complex pipeline model under the background of Industry 4.0 is designed, extracting and rendering the wireframe model and extracting background of the complex pipeline video. We obtain the angle information of the corner points of the complex pipeline surface, extract and match the feature of the dense point cloud, and construct the 3D point cloud data mosaic model. The pipe surface is generated by using double-nodal B-spline. The experimental results show that the precision and stability of the proposed method are high. In the early stage, the proposed method uses ISS feature extraction algorithm to extract feature of point cloud data, which improves the positioning accuracy effectively and enhances the 3D point cloud intelligent stitching speed.

Industry 4.0 is recognized as the fourth-generation industrial revolution, which can drive the development of the world’s smart manufacturing industry. The information security in the implementation of Industry 4.0 strategy was analyzed in this article. The specific measures to ensure the information security of Industry 4.0 were proposed from the perspectives of industrial control system security strategy, security measures, security awareness, data security protection, data security responsibility, and encryption technology. Furthermore, the distributed control system and IT network security communication platform construction are applied to solve the information security problem of Industry 4.0. The adoptable solutions will provide an important reference to maintain the information security of Industry 4.0.

The service innovation based on the cyber-physical system is a trend in the future manufacturing industry. In this article, the servicing functions involved in the manufacturing industry under the environment of industrial big data were analysed. In addition, the combination of the needs, environment and services of industrial big data were described. Furthermore, the intelligent forecasting tools to manage industrial big data, increase the transparency of industrial production, and improve work efficiency were proposed to adopt for the application of service innovation.