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

Year 2023, , 141 - 151, 20.10.2023

Sair Kahraman , Masoud Rostami , Behnaz Dibavar

https://doi.org/10.30797/madencilik.1310876

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.

Keywords

Coal mining, Roadheader, Machine utilization time

Supporting Institution

TÜBİTAK

Project Number

217M740

Thanks

The authors thank TUBITAK (The Scientific and Technological Research Council of Turkey) for the support of the project (Project No. 217M740). The authors also thank Park Termik Elektrik Sanayi ve Ticaret A.Ş., Hattat Enerji ve Maden Ticaret A.Ş., Polyak Eynez Enerji Üretim Madencilik San. ve Tic. A.Ş., İmbat Madencilik Enerji Turizm San. Tic..A.Ş., Demir Export A.Ş., YS Madencilik San. ve Tic. Ltd. Ş. and Kömür İşletmeleri A.Ş. for allowing the field studies.

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