Research Article | Open Access | Download PDF
Volume 73 | Issue 12 | Year 2025 | Article Id. IJETT-V73I12P113 | DOI : https://doi.org/10.14445/22315381/IJETT-V73I12P113Bivariate 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.
References
[1] Hemant
Agrawal, and A.K. Mishra, “Evaluation of Initiating System by Measurement of
Seismic Energy Dissipation in Surface Blasting,” Arabian Journal of
Geosciences, vol. 11, no. 13, 2018.
[CrossRef] [Google
Scholar] [Publisher
Link]
[2] Prakash Amar, Murthy Vemavarapu
Mallika Sita Ramachandra, and Singh Kalendra Bahadur, “Performance Simulaton of
Surface Miners with Varied Machine Parameters and Rock Conditions: Some
Investigations,” Journal of Geology and Mining Research, vol. 5, no. 1,
pp. 12-22, 2013.
[CrossRef] [Google
Scholar] [Publisher
Link]
[3] Rajesh Bhatta, Nilima Dash, and
Bibhuranjan Nayak, “Characters of Liptinites in Different Seams of Talcher
Coalfield, Odisha, India,” Journal of the Geological Society of India,
vol. 98, no. 2, pp. 193-197, 2022.
[CrossRef] [Google
Scholar] [Publisher
Link]
[4] Nuh Bilgin et al., “Dominant Rock
Properties Affecting the Performance of Conical Picks and the Comparison of
Some Experimental and Theoretical Results,” International Journal of Rock
Mechanics and Mining Sciences, vol. 43, no. 1, pp. 139-156, 2006.
[CrossRef] [Google
Scholar] [Publisher
Link]
[5] K. Dey, and A.K. Ghose, “Selecting a Surface
Miner - An Algorithm,” Journal of Mines, Metals and Fuels, vol. 57, no.
9, pp. 282-287, 2009.
[Google
Scholar]
[6] K. Dey, and P. Sen, “Continuous
Surface Miner in Mining Limestone and Coal in India - A Comparative Study,” Journal
of Mines, Metals and Fuels, vol. 56, no. ¾, pp. 51-54, 2008.
[Google
Scholar] [Publisher
Link]
[7] A.K. Ghose, “Surface Miner Operations at
Lakhanpur Opencast Project: A Preliminary Evaluation,” International Seminar
on ‘‘Quality, Productivity and Environment-the Challenges”, Bhubaneswar,
IMMA, 2000.
[Google
Scholar]
[8] R.M.
Goktan, and N. Gunes, “A Comparative Study of Schmidt Hammer Testing Procedures
with Reference to Rock Cutting Machine Performance Prediction,” International
Journal of Rock Mechanics and Mining Sciences, vol. 42, no
3, pp. 466-472, 2005.
[CrossRef] [Google
Scholar] [Publisher
Link]
[9] Shrikant M. Harle, and Rajan L. Wankhade,
“Machine Learning Techniques for Predictive Modelling in Geotechnical
Engineering: A Succinct Review,” Discover Civil Engineering, vol. 2, no.
1, pp. 1-21, 2025.
[CrossRef] [Google
Scholar] [Publisher
Link]
[10] I.O. Jones, and S. Kramadibrata, “An
Excavating Power Model for Continuous Surface Miners,” AusIMM Proceedings,
vol. 300, no. 2, pp. 33-39, 1995.
[Google
Scholar] [Publisher Link]
[11] Sarma
S. Kanchibotla, and Andrew Scott, “A Study of the Influence of Buffering on
Coal Edge Loss and Dilution from Cast Blasting,” Fragblast, vol. 3, no.
4, pp. 365-375, 1999.
[CrossRef] [Google
Scholar] [Publisher
Link]
[12] E.A.
Khoyutanov, and V.L. Gavrilov, “Coal Quality Control in Mining
Complex-Structure Deposits,” Journal of Mining Science, vol. 55, no. 3,
pp. 399-406, 2019.
[CrossRef] [Google
Scholar] [Publisher
Link]
[13] M.
Kiani et al., “Risk Assessment of Blasting Operations in Open Pit Mines using
FAHP Method,” Mining of Mineral Deposits, vol. 13, no. 3, pp. 76-86,
2019.
[CrossRef] [Google
Scholar] [Publisher
Link]
[14] Suseno
Kramadibrata, The Influence of Rock Mass and Intact Rock Properties on the
Design of Surface Mines with Particular Reference to the Excavation of Rock,
Part-I, II and III, School of Civil Engineering, Curtin University of
Technology, 1996.
[Google
Scholar] [Publisher
Link]
[15] Fred
H. Kulhawy, “Stress Deformation Properties of Rock and Rock Discontinuities,” Engineering
Geology, vol. 9, no. 4, pp. 327-350, 1975.
[CrossRef] [Google
Scholar] [Publisher
Link]
[16] Romil
Mishra, Arvind Kumar Mishra, and Bhanwar Singh Choudhary, “High-Speed Motion
Analysis-Based Machine Learning Models for Prediction and Simulation of Flyrock
in Surface Mines,” Applied Sciences, vol. 13, no. 17, pp. 1-33, 2023.
[CrossRef] [Google
Scholar] [Publisher
Link]
[17] V.M.S.R. Murthy et al., “Development of a
Cuttability Index of Surface Miner for
Performance Prediction in Different Geomining Conditions,” International
Symposium on Rock Mechanics and Geo-Environment in Mining and Allied Industries,
Banaras Hindu University, Varanasi, pp. 12-14, 2009.
[Google
Scholar] [Publisher
Link]
[18] Chiara Origliasso, Marilena Cardu,
and Vladislav Kecojevic, “Surface Miners: Evaluation of the
Production Rate and Cutting Performance Based on Rock Properties and Specific
Energy,” Rock Mechanics and Rock Engineering, vol. 47, no. 2, pp.
757-770, 2014.
[CrossRef] [Google
Scholar] [Publisher
Link]
[19] José
Padarian, Budiman Minasny, and Alex B. McBratney, “Machine Learning and Soil
Sciences: A Review Aided by Machine Learning Tools,” Soil, vol. 6, no.
1, pp. 35-52, 2020.
[CrossRef] [Google
Scholar] [Publisher
Link]
[20] Katarzyna
Pentoś et al., “Evaluation of Multiple Linear Regression and Machine Learning
Approaches to Predict Soil Compaction and Shear Stress based on Electrical
Parameters,” Applied Sciences, vol. 12, no. 17, pp. 1-17, 2022.
[CrossRef] [Google
Scholar] [Publisher
Link]
[21] G.K.
Pradhan, Om Prakash, and N.R. Thote, “Blast Free Mining in Indian Surface Coal
Mines-Current Trend,” Mine Planning and Equipment Selection: Proceedings of
the 22nd MPES Conference, Dresden, Germany, 14th - 19th
October 2013, pp. 335-357, 2014.
[CrossRef] [Google
Scholar] [Publisher
Link]
[22] A.
Prakash, and V.M.S.R. Murthy, “Hierarchy of Parameters Influencing Cutting
Performance of Surface Miner through Artificial Intelligence and Statistical
Methods,” Current Science, vol. 112, no. 6, pp. 1242-1249, 2017.
[CrossRef] [Google
Scholar] [Publisher
Link]
[23] Amar
Prakash, and Vemavarapu M.S.R. Murthy, “Prediction of Cutting Speed of Surface
Miner for Coal and Limestone Production under Varied Rock Mass Conditions,” Journal
of the Geological Society of India, vol. 100, no. 8, pp. 1122-1128, 2024.
[CrossRef] [Google
Scholar] [Publisher
Link]
[24] A.
Prakash, V.M.S.R. Murthy, and K.B. Singh, “Chip Size Characterization for
Selecting Optimum Production Parameters of Surface Miner Operating in a Coal
Mine,” Current Science, vol. 108, no. 3, pp. 422-426, 2015.
[Google
Scholar] [Publisher
Link]
[25] Lvinash Prasad, Sandeep Prasad, and G.K.
Pradhan, “Performance Appraisal of Surface Miner in Opencast Mines: A Case
Study,” The Indiln Mining and Engineering Journll.
[Google
Scholar]
[26] Paul
Segall, “Rate‐Dependent Extensional Deformation Resulting from Crack Growth in
Rock,” Journal of Geophysical Research: Solid Earth, vol. 89, no. B6,
pp. 4185-4195, 1984.
[CrossRef] [Google
Scholar] [Publisher
Link]
[27] Alokranjan
Senapaty, and P. Behera, “Stratigraphic Control of Petrography and Chemical
Composition of the Lower Gondwana Coals, Ib-Valley Coalfield, Odisha, India,” Journal
of Geoscience and Environment Protection, vol. 3, no. 4, pp. 56-66, 2015.
[CrossRef] [Google
Scholar] [Publisher
Link]
[28] A.
Singh et al., “Failure Analysis and Performance Improvement using Surface Miner
on Field Breakdown Data: A Case Study,” Industrial Engineering Journal,
vol. 12, no. 9, pp. 1-31, 2019.
[Google Scholar]
[29] Nilesh
P. Singh, Aarif Jama, and Nawal Kishore. “Impact of Coal Quality on Longevity
of Picks of Surface Miner-A Case Study,” International Conference on Deep
Excavation, Energy Resources and Production, Varanasi, India, vol. 170,
2017.
[Google
Scholar]
[30] Nilesh
Pratap Singh et al., “Impact of Surface Miner Utilisation on Production
Efficiency in Opencast Coal Mines Using Least Squares Method: A Case
Study,” Journal of The Institution of Engineers (India): Series D, vol.
105, no. 1, pp. 567-580, 2023.
[CrossRef] [Google
Scholar] [Publisher
Link]
[31] B.
Tiryaki, and A. Cagatay Dikmen, “Effects of Rock Properties on Specific Cutting
Energy in Linear Cutting of Sandstones by Picks,” Rock Mechanics and Rock
Engineering, vol. 39, no. 2, pp. 89-120, 2006.
[CrossRef] [Google
Scholar] [Publisher
Link]
[32] Ashish
Kumar Vishwakarma et al., “Investigations on the Influence of Applied Thrust on
Rock Penetration Rate by a Raise Boring Machine Using Numerical Simulation and
Experimental Trials,” Mining, Metallurgy and Exploration, vol. 40, no.
4, pp. 1187-1197, 2023.
[CrossRef] [Google
Scholar] [Publisher
Link]
[33] J.B.
Walsh, “The Effect of Cracks on the Compressibility of Rock,” Journal of
Geophysical Research, vol. 70, no. 2, pp. 381-389, 1965.
[CrossRef] [Google
Scholar] [Publisher
Link]
[34] Thomas
Welchowski et al., “Techniques to Improve Ecological Interpretability of
Black-Box Machine Learning Models: Case Study on Biological Health of Streams
in the United States with Gradient Boosted Trees,” Journal of Agricultural,
Biological, and Environmental Statistics, vol. 27, no. 1, pp. 175-197,
2021.
[CrossRef] [Google
Scholar] [Publisher
Link]
[35] Manish
Yadav et al., Surface Miner: A Green Approach to Coal Production in Indian
Surface Coal Mines, Green Innovation, Sustainable Development, and Circular
Economy, CRC Press, 1st ed., pp. 17-32, 2020.
[Google
Scholar] [Publisher
Link]