Gravimetric method was conducted to assess shearer mining production output, which could adjust shearer gesture anytime and get shearer under real time control, weighing only after the completion of the production process. But, it cannot monitor shearer real time efficiency. According to the process of walking the shearer in the coal mining process, speed, temperature, cutting motor cutting current and temperature parameters combining the use of multivariate statistical theory, established mathematical model and predicted mining coal production model to the shearer control process, the online ratio between shearer production and its energy could be monitored, this assessment can optimize shearer efficiency and get more real time control of shearer.  This thesis utilized the multivariate statistical theory to make a multivariate statistical mode, which was used to predicate and control the output of the mine shearer through measuring the output parameters of mine shearer, making mine shearer’s output become more mechanized and intellectualized.