The Application and Prospect of Machine Learning in Improving Production Efficiency

Abstract

With the continuous development of manufacturing industry, enhancing production efficiency has become the core link of enterprise competition. Machine learning, as a subfield of artificial intelligence, has been widely applied in the production field. It assists decision-making through intelligent driving of data, thereby promoting the optimization of production processes. This article analyzes the core technologies of how machine learning can improve production efficiency, including time series analysis, intelligent supply chain, and inventory management. Furthermore, the practical applications of machine learning in demand forecasting, production scheduling, quality control, resource allocation, and energy efficiency optimization were explored. In the future, as technologies like deep learning and reinforcement learning advance, machine learning will see broader applications in production, especially in areas such as multi-source data fusion, real-time data processing, and adaptive production systems, which hold significant potential. The popularization of automated decision support systems will further promote the improvement of production efficiency.