Advanced Manufacturing Data Space Visualization Based on PCA-Radviz Model

Abstract

Radviz method is a more commonly used method to visualize multi-dimensional data into a two-dimensional plane, but if there are too many dimensions, Radviz will be shortcomings of overlapping of data performance. At present, China’s industry has entered the stage of advanced manufacturing. With the development of Internet technology and big data technology, a big data environment has been created along with the manufacturing supply chain, and the advanced manufacturing data are always belonging to a high-dimensional data, it is difficult to present by Radviz, this paper proposes a visualization algorithm for advanced manufacturing based on principal component analysis(PCA) and Radviz visualization method, which can optimize the expression of multi-dimensional time series on a two-dimensional plane after dimensionality reduction using PCA. Finally, the paper uses power supply as a visual example to verify the proposed mode, and the results show that the proposed model can indeed provide decision-makers with more intuitive decision-making information.