Research on performance evaluation of intelligent manufacturing enterprises supported by machine learning and big data technology

Intelligent manufacturing, as a pillar of the manufacturing industry, provides crucial support for achieving China's strategic goal of becoming a manufacturing powerhouse. The operation and management process of intelligent manufacturing enterprises requires a large amount of capital investment, and the efficiency of capital utilization directly affects the economic benefits of intelligent manufacturing enterprises. Relevant enterprises continue to improve the performance evaluation mechanism and enhance their performance evaluation ability, so as to effectively promote the realization of corporate strategic objectives and continue to become a solid support for the steady operation of China's economy. On this basis, the performance of intelligent manufacturing enterprises was deeply explored, and a set of performance evaluation indicator framework for intelligent manufacturing enterprises was established by using machine learning and big data technology. Through empirical analysis, machine learning methods are introduced into performance evaluation to establish an assessment mechanism for intelligent manufacturing enterprises that is suitable for China's national conditions. For ridge regression, lasso regression, and elastic network regression in machine algorithm, we have conducted in-depth research and built a set of performance evaluation system using the model of lightGBM. Construct a framework of performance evaluation system for intelligent manufacturing enterprises based on machine learning and big data technology support, and use TOPSIS method to conduct empirical analysis, thus further highlighting the importance of evaluation and feedback mechanism for intelligent manufacturing enterprises.