{"title":"煤矿掘进机机器使用时间评价:回归与人工神经网络分析","authors":"Sair KAHRAMAN, Masoud ROSTAMİ, Behnaz DİBAVAR","doi":"10.30797/madencilik.1310876","DOIUrl":null,"url":null,"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.","PeriodicalId":37481,"journal":{"name":"Scientific Mining Journal","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Evaluating machine utilization times for roadheaders used in coal mines: Regression and artificial neural network analyses\",\"authors\":\"Sair KAHRAMAN, Masoud ROSTAMİ, Behnaz DİBAVAR\",\"doi\":\"10.30797/madencilik.1310876\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":37481,\"journal\":{\"name\":\"Scientific Mining Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientific Mining Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30797/madencilik.1310876\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Mining Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30797/madencilik.1310876","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Engineering","Score":null,"Total":0}
Evaluating machine utilization times for roadheaders used in coal mines: Regression and artificial neural network analyses
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.
期刊介绍:
Scientific Mining Journal, which is published i n open access electronic environment and i n printed, is a periodical scientific journal of Union of Chambers of Turkish Engineers and Architects Chamber of Mining Engineers. The name of the journal was "Mining" until June 2016 and it has been changed to "Scientific Mining Journal" since September 2016 because it can be confused with popular journals with similar names and the ISSN number has been updated from 0024-9416 to 2564-7024. Scientific Mining Journal, published four times a year (March-June-September-December), aims to disseminate original scientific studies which are conducted according to the scientific norms and publication ethics at national and international scale, to scientists, mining engineers, the public; and thus to share scientific knowledge with society. The journal is in both Turkish and English. The journal covers theoretical, experimental, and applied research articles, which reflects the findings and results of an original research i n the field of mining engineering; review articles, which assess, evaluates, and interprets the findings of a comprehensive review of sufficient number of scientific articles and summarize them at present information and technology level; technical notes, which may be defined as a short article that describes a novel methodology o r technique; a case studies, which are based on the theoretical o r real professional practice and involves systematic data collection and analysis.