Abstract
According to vehicle multi-source quality safety data information, the key quality safety factors for automobile defect risk assessment are extracted, the association relationship map is established, and the vehicle defect evaluation index system is systematically constructed. On the basis of the correlation and optimization of key quality safety factors and index systems, a multi-dimensional cluster of defective vehicle quality and safety information is established by utilizing big data technology and so forth. Based on the historical automobile defect data information, the clustering method has been employed and formed more than 4000 typical automobile defect cases, association analysis on multi-source quality safety data information is conducted and developed vehicle defect risk assessment system is designed which provides data and technical support for rapid warning of vehicle defect risk.
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