Manufacturing Audit Quality Analysis Model Based on Data Mining Technology

Abstract

As our country's economic development enters a new normal, the original manufacturing development model can no longer meet the needs of current economic development, and it is urgent to accelerate the transformation of the manufacturing industry. At present, the country's supply-side structural reforms are deepening, and listed manufacturing companies are the most important backbone in terms of scale and innovation opportunities. Data mining technology is used to study the impact of quality control on corporate performance. Listed companies have a positive impact on the further realization of transformation and upgrading and the improvement of corporate performance. This article aims to study the manufacturing audit quality analysis model based on data mining technology, and adopts the analysis method of the combination of supervisory research and empirical analysis, from the perspective of supervisory research, summarizes the theory of internal audit quality and company performance in the research process, and summarizes predecessors' research results and research ideas. The experimental data in this article shows that the average quality of internal audit information disclosure is 3.1156, indicating that the audit disclosure status of listed companies selected by the Shenzhen Stock Exchange is good, and to a certain extent reflects the quality level of some internal controls.