The paper intends to generate a universal model to predict the performance of roadheaders for all kinds of rock formations. In this regard, we first take into account the outcomes of previous attempts to explore the performance of roadheaders in Tabas Coal Mine project (the largest and fully mechanized coal mine in Iran). During those investigations, rock mass brittleness index (RMBI) was defined in order to relate the intact and rock mass characteristics to machine performance. The statistical analysis of data acquired from Tabas field demonstrated that RMBI was highly correlated to instantaneous cutting rate (ICR) of roadheaders ( R ² = 0.92). With the aim to construct a universal model for predicting the roadheader performance, we have now tried to establish a database consisting measured cutting rate of roadheaders as well as the data gathered from field studies of Tabas Coal Mine project and Besiktas, Kurucesme, Baltalimani, Eyup and Halic tunnels in Turkey. A broad modeling and analysis found a fair relationship, resulting in a new universal predictive model to predict the cutting rate of roadheaders with correlation of 0.73 ( R ² = 0.73). The application of local and universal models at Tabas Coal Mine showed a remarkable difference between measured and predicted ICR. The mean relative error of 0.359% was found with universal model but it represented lower value (mean relative error of 0.100%) while using local model. It can thus be concluded that instead of generating a universal model, separate localized models for different ground and machine conditions should be developed to improve the accuracy and reliability of the performance prediction models.
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Ebrahimabadi et al. (2012) studied this question.
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