Empirical Models for Estimating Performance and Operational Parameters of Raise Boring Machine in Mining Applications

S Yagiz, Aydin Shaterpour-Mamaghani, Aitolkyn Yazitova, K. Yermukhanbetov, Engin Dogan, Tayfun Erdogan, Hanifi Copur

2021

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.1088/1755-1315/833/1/012129
Data confidence 70 medium
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Abstract

Abstract Raise boring machines (RBMs) are commonly utilized for drilling of shaft and other inclined structures in mining and civil applications. This paper aim to introduce several empirical equations to estimate the performance and operational parameters of RBMs. For the aim, datasets having rock properties including uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), brittleness (BI), rock quality designation (RQD), elastic modules (E) and Poisson ratio (v); and also RBMs operational parameters including Instantaneous penetration rate (IPR), Specific Energy (SE), Pushing Force (Fpush), reamerhead power (Pw) and rotational speed (RPM), were established from published case studies. After that, re-established dataset was utilized to develop multiple regression models to predict the performance and operational parameters of RBM. It is found that IPR, SE, Fpush, Pw and RPM could be estimated using several alternative rock properties with coefficients of determination ranging from 0.77 to 0.95. Based on utilized dataset, it is also concluded that RQD and BI are the most common rock properties for estimating the performance and operational parameters of RBMs.