International Journal of Engineering
Trends and Technology

Research Article | Open Access | Download PDF
Volume 73 | Issue 12 | Year 2025 | Article Id. IJETT-V73I12P113 | DOI : https://doi.org/10.14445/22315381/IJETT-V73I12P113

Bivariate Analysis of the Geotechnical Properties and the Key Performance Indicators of the Surface Miners


Om Prakash Singh, P Y Dhekne, Manoj Pradhan

Received Revised Accepted Published
12 Aug 2025 18 Nov 2025 25 Nov 2025 19 Dec 2025

Citation :

Om Prakash Singh, P Y Dhekne, Manoj Pradhan, "Bivariate Analysis of the Geotechnical Properties and the Key Performance Indicators of the Surface Miners," International Journal of Engineering Trends and Technology (IJETT), vol. 73, no. 12, pp. 162-173, 2025. Crossref, https://doi.org/10.14445/22315381/IJETT-V73I12P113

Abstract

An increase in the population and operating mining projects near cities, towns, and villages, many opencast mines are planning blast-free operations through the application of surface miners. These machines are costly. Hence, the assessment of the geotechnical parameters that influence the performance of the machine is a prerequisite. Accordingly, research was planned and executed in the opencast coal projects of Mahanadi Coalfields Ltd. (MCL) to investigate the effect of geotechnical parameters, viz. Uniaxial Compressive Strength (UCS), Cerchar Abrasivity Index (CAI), Young’s Modulus (E), and in-situ P-wave Velocity (IVP), on two key performance indicators of surface miner - Normalised Production Rate (NPR) and Pick Consumption per 1000 t (PCM). A database comprising the above-stated geotechnical parameters and the key performance indicators of the surface miner was generated. Bivariate regression analysis was conducted on the database, and as a result, it was observed that CAI predominantly influences the NPR and PCM with R² = 0.91 and 0.89, respectively. UCS follows with R² = 0.88 for NPR and 0.80 for PCM, while IVP (R² = 0.85 and 0.77) and E (R² = 0.82 and 0.75) show comparatively lower but significant effects. These findings establish CAI as the dominant parameter affecting both productivity and tool wear, followed by UCS, IVP, and E. Accurate determination of these parameters is therefore essential for reliable performance prediction, optimal machine selection, and cost-effective surface mining operations in the geotechnical set-up of the coal seams in MCL.

Keywords

Cerchar Abrasivity Index, In-Situ P-wave Velocity, Performance Indicators of the Surface Miners, Uniaxial Compressive Strength, Young’s Modulus of Elasticity.

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