Research on the Human–Machine System Efficiency in Deep Mining Under the Coupling Effect of Multiple Factors

Currently, deep mining has become the development trend of underground mines, and the harsh working environment underground seriously affects the efficiency of personnel and equipment operations. The operational efficiency of the human–machine system composed of personnel and equipment is not only affected by the status of personnel and equipment, but also closely related to the interaction between human–machine–environment. How to ensure the efficient operation of human–machine systems has become the key to improving the quality and efficiency of mines. Therefore, in order to analyze the interaction relationship between human–machine–environment in the process of human–machine system operation and explore the variation law of human–machine system efficiency. This paper constructs a deep mining human–machine system efficiency system dynamics model under the multi-factor coupling effect of deep well mining, guided by system dynamics theory, and obtains the variation laws of system efficiency under single-factor changes and multi-factor coupling effects. The research results solve the problem of difficulty in quantitatively describing the logical and quantitative relationships between various elements in the study of human–machine system efficiency, providing new ideas for the study of underground work efficiency. Through mathematical modeling, the temperature threshold for the efficient operation of the human–machine system is determined, and the quantitative relationships among temperature, humidity, and wind speed are elaborated, providing a reference for ensuring the efficient operation of the human–machine system in deep mining.