Surface quality evaluation based on roughness prediction model

The manufacturing process is the key link that concerns product quality. Considering the non-ideal state of processing and raw materials, the processing defects cannot be completely eliminated, but it is possible to regulate the defects accumulated in product within the product performance requirements through optimizing the technology and controlling the processing. That is, to guarantee the maximum tolerance to defects during the product's reliable life cycle. In this paper, the representative roughness defect during turning is selected as the key control object of the typical coupling process. On the foundation of the traditional roughness prediction theory based on deterministic process parameters, the roughness prediction model that comprehensively considers the random vibration factor of turning process is established, and the corresponding turning test collected data is designed for analysis as well as research. According to the results, the selected input information and predicted surface roughness are in good consistency. It shows that the surface roughness will be affected by the factors such as cutting amount, tool state and vibration. For this reason, it is available to instantly predict the surface roughness of machined in practical process through the acquisition of vibration signals.