Evaluating machine utilization times for roadheaders used in coal mines: Regression and artificial neural network analyses

Abstract

Roadheaders are extensively utilized for tunnel heading rock engineering applications all over the world. To create a work plan and calculate costs, it is critical to forecast roadheader performance as precisely as possible. Machine utilization time (MUT) is required for the calculation of daily advance rate of roadheaders. This paper investigates the values of MUT for roadheaders used in underground coal mines. The performance measurements were conducted on fifty different locations for axial machines and thirty-nine different locations for transverse machines. MUT values vary from 15 % to 37.5 % with an average of 26.3 % for axial roadheaders, and vary from 6.9 % to 37.9 % with an average of 18.4 % for transvers roadheaders. The average MUT is 25.4% for all measurements. The percentage of average support time approximately equals to the average MUT. Multiple regression and artificial neural network models were also developed for estimating MUT. Concluding remark is that the determined MUT values and the derived estimation models for roadheaders will be very useful for coal miners.