Application of drone technology combined with LiDAR and Virtual Reality/Augmented Reality in surface mining operational optimization is growing on a high trajectory. The mining sector has demonstrated increased interest in using drones for everyday tasks such as bench face mapping, dump planning, dragline dump disposal as per balance diagram in surface mining. One of the key requirements in dragline mining is the application of 3-dimensional mapping of the dragline dump area and dump space management for the dragline dump in a safe and efficient manner. The drone can assist in judicious disposal of a dump near the dragline bench mining keeping in mind the available dump/pit space and slope stability requirements. This research article presents a review of drone technology and how LiDAR and Virtual Reality/Augmented Reality Technology based on cloud computing architecture can accelerate the mine planning activity for dragline dump disposal for a simple side cast mining method. Furthermore, it discusses the current applications of AI-driven 3D computer vision techniques in automating data analytics with point clouds for the extraction of terrain parameters and plan efficient dump disposal strategies by proper positioning of dragline in a large surface mine.

Tunnel boring machine (TBM) has been in focus for the last few decades and is currently the most preferred excavation method for metro, hydro and irrigation tunnels. Tunnelling in hard and abrasive rock conditions, in particular, is adversely affected by a very low advance rate coupled with increased TBM disc cutter failures and cutterhead jamming, seeking an in-depth understanding of the design and operational processes of the boring components of the TBM. The cutterhead and disc cutter are the critical boring components of the machine, influencing the boring process significantly. These components directly interact with the rock and hugely influence the machine’s efficiency. This paper encapsulates a review of prior studies related to disc cutter design and the cutterhead design for hard rock TBM tunnelling. A design methodology for designing and selecting a disc cutter and a cutterhead is suggested. The design methodology has been applied for a hard rock tunnelling case, and suitable design specifications for the boring components were arrived at. The disc cutter and cutterhead specifications designed based on the suggested methodology closely match with that of deployed TBM specifications. It may be observed that except for the case of high-strength and high-abrasive rock (greyish quartzite), for the rest of the rocks, the suggested design can meet the desired advance rates.

Bord and pillar method of mining continues to be a major operation in India with about 160 mines producing 35 MT of coal. Owing to the exhaustion of near-surface deposits, environmental impacts and land acquisition issues associated with surface mining, underground coal mining is expected to take a leap in the next decade. Weak and layered roof strata in underground mining play a significant role in roof failures in development headings affecting both safety and productivity. Despite well-defined support design guidelines based on CMRI-ISM RMR, roof failures are still a cause of great concern. In this research, firstly, a risk matrix has been framed on the basis of stable and unstable roof conditions for evaluating the potentiality of roof failure. This was followed by the development of a modified Rock Mass Classification System (RMRdyn) considering Seismic velocity of rocks as one of the key parameters. A modified empirical relationship for rock load (RL) and a handy nomogram has been developed based on input parameters, namely, P-wave velocity, structural features, slake durability and groundwater condition. A guideline for roof support design has been framed based on rock load computed for RMRdyn values ranging from 25 to 70. The developed models have been validated by statistical tools. The study also presents the risk classes to enable rock engineers to design more rational support systems in coal mine development headings.

Effective monitoring of spoil pile heights resulting from dragline dumps is critical in mining space management both safely and productively, particularly, during active overburden (OB) removal. This study addresses this concern by replicating stable dump piles in alignment with the dragline balancing diagrams at a dynamic scale, optimizing in-pit volume use. Real-time tracking of dump pile heights ensures efficient dump disposal management, garnering attention in the mining industry. Monitoring dump height and shape during OB disposal near the dragline is vital. It is proposed to employ an experimental setup, consistently dumping specific volume samples from predefined heights at constant velocities. The technique uses You Only Look Once (YOLO) for dump pile height measurements. A benchmark dataset is created, encompassing various dragline dump configurations. YOLO achieves an F1-confidence score of 84.6% and a mean average precision (mAP) value of 99.49% in accurately recognizing dump profiles. To validate its reliability, output is compared with photogrammetry (SFM-MVS and NeRF). Employing 2D computer vision (AI) on simulated video data offers a fast, cost-effective, real-time solution for secure dump pile profile detection and height measurement, enhancing dragline mining efficiency with stable and safe dump heights as per design.

Firing sequence of blastholes in blasting is an inherent part of the blast design for various reasons that range from the spatial requirements to the control of throw during blasting in surface mines. Despite several such patterns in vogue, role of firing sequences in defining the size of fragmented block sizes is not properly understood. The V-type firing pattern is believed to improve blast fragmentation because of the collision of moving fragments during the blasting process, thus resulting in further breakage. There are practically negligible studies that substantiate this assertion. The role of V-type firing pattern has been explored in this paper with simple logic and some field data. It is observed that the V-type firing pattern produces better fragmentation and controls the throw during blasting. A comparison with diagonal firing pattern, in controlled experiments, makes it evident that V-type firing pattern can be used to advantage for fragmentation improvement.

Rock engineering for creating underground spaces involves drilling at various scales and the demand for the same is growing exponentially for meeting various engineering and societal needs. Rock drillability was comprehensively assessed for weak, abrasive, hard, and hard-abrasive rocks from Indo-Bhutan origins. An experimental methodology to measure the expected bit life along with penetration rate (PR) using a single test method was developed. Petrographic assessments, phase-wise drillability and bit wear (BW) parameters indicated that PR varied from 0.33 to 19.3 mm/min with about 90% PR reduction during the active drilling phase. Stress levels under the bit remained asymptotic below 40% of BW flat-width percentage. The mean penetration rate increased by 83% with increased thrust and drill productivity enhanced up to 1.6 times with the proposed Compendious Index for Drillability (CID). Field-scale studies indicated that the CID has better explained the variance in field PR and bit life up to 76.7% compared to popularly used DRI and CHI indices. Developed CPRI- and CID-based drillability characterization systems aided in estimating the field PR and bit life more accurately apart from their applicability vis-à-vis limitations in different geo-structural environments.

Performance of TBM is significantly influenced by the ground conditions and machine variables. To achieve an optimum rate of penetration (ROP) during TBM excavation, it is important to assess the interaction between rock mass properties and machine operational/performance variables. This paper presents a systematic analysis of TBM performance based on the data collected from the MetroLine-3 UGC-01 project in Mumbai, India, and proposes a few performance prediction models for the Deccan Traps. The current work attempted to bring out the combined effect of RQD × Js as a single predictor variable while suggesting a reliable RSA modeling technique which considers the simultaneous interaction of variables. The database consisted of engineering-geological and machine variables; the selected variables were analyzed using artificial neural networks (ANN) for identifying the significant variables. Subsequently, multivariate regression (MVRA) and response surface analysis (RSA) were utilized to develop a model for predicting TBM ROP. The first model developed using MVRA as a function of rock mass variables yielded a coefficient of determination (R2) of 0.80, whereas the second composite model developed as a function of geological and machine variables yielded an R2 of 0.85. The third model was developed utilizing RSA which resulted in 2FI (two-factor interaction) model with improved R2 of 0.88. Further, the best-performing RSA model accuracy is compared with the existing models and subsequently validated using new datasets and yielded an R2 of 0.79. The developed model equation indicates that UCS, RQD × Js, and thrust variables show significant influence on the TBM ROP.

Raises are vertical or inclined openings made to connect two levels of an underground metalliferous mine. They are developed using drilling and blasting-based technique or by mechanical means. Raise boring machines (RBM) have evolved in recent years, which provide quicker and safer raise excavation. The penetration rate using RBM has influenced applied thrust. The required thrust to enhance penetration rate with optimal use of energy would be different under varying geological and geotechnical conditions. In this study, the influence of applied thrust on penetration rate using RBM has been investigated. The investigation has been made for two different rock types, amphibolite (AMP) and garnet-biotite-sillimanite-gneiss (GBSG). The numerical simulation model was developed for this purpose using Ansys-Explicit Dynamics. The induced tensile stress under different conditions of applied thrust has been analysed in the calibrated numerical model. The model output shows the power trend between the parameters. The experimental data on penetration rate was also collected along with the respective operational parameters. A statistical analysis has been carried out for the gathered data. The analysis of data also shows a power trend between thrust per cutter and penetration rate in both rock types and hence validates the numerical simulation-based output. Based on the outputs of the numerical simulation and empirical study of the experimental data, the optimum thrust per cutter for excavation in both rock types is in the range of 12–14 tons. The approach used in this study can be helpful for predicting the optimal operational parameters of raise boring machines under different geological/geotechnical conditions.

Weak, layered, and fragile rock mass formation, if not supported properly, is subject to roof failure thereby affecting safety and productivity in underground coal mines. Though Central Mining Research Institute – Indian School of Mines Rock Mass Rating (CMRI-ISM RMR) based well-defined support design guidelines are established, still occurrence of roof failures in underground coal mines is a real matter of concern for mining engineers and researchers. Numerical modeling techniques are successfully used by several researchers by simulating rock mass condition for stability assessment of mine openings. The analysis becomes crucial in case of weak and fragile rock formation. The present research envelops the determination of 31 cases of rock load by CMRI-ISM RMR under different geo-mining conditions followed by the development of modified Rock Mass Rating (RMR), i.e., rock mass rating dynamic (RMRdyn) by incorporating P-wave velocity as a new parameter. The rock load determined using RMRdyn and numerical models was correlated and found in close agreement. In addition, the deviation in rock load determined by all the three approaches, i.e., CMRI-ISM RMR, numerical modeling, and RMRdyn, was compared with the actual field data. The percentage deviation obtained in RMRdyn and numerical modeling is less compared to CMRI-ISM RMR.

Tunnel boring machine (TBM) is a popular rock cutting machine for rapid construction of tunnels. This paper mainly dwells on the excess cutter wear and low penetration rates encountered while tunnelling through hard and abrasive rock in a head race tunnel being driven for hydel power generation. Wear prediction in disc cutters with its mechanism was reviewed. Field performance data and laboratory characterization of rock were done for analyzing the causative factors. This was followed by data analysis using a multilayer shallow neural network (MSNN) for identifying the key parameters and their influence on the output parameters (cutter wear and rate of penetration). Five major process control parameters including two machine parameters, namely, thrust and torque, one design parameter, i.e., radial position of cutter and two rock parameters namely uniaxial compressive strength (UCS) and Cerchar abrasivity index (CAI) are considered in the study. Rock type is kept constant (quartzite) to analyze the influence of the machine operating parameters on the cutter penetration rate and the cutter wear. Two different scenarios were analyzed. The correlation coefficients obtained between output and target for two cases investigated were 0.927 and 0.965, respectively. Sensitivity analysis of the input parameters on the output parameter is also carried out. For validation of the result, response surface method (RSM) was used for the analysis of historical data. Both MSNN and RSM predict the influence of key variables affecting cutter wear (CW) and rate of penetration (RoP) with a good confidence. In a given rock setting, it is possible now to fix the optimal values of Thrust and Torque to control the cutter wear while maintaining an acceptable rate of TBM penetration.

Underground metro projects in Mumbai city has witnessed huge surge in the construction since last few years and large number of shielded tunnel boring machines were deployed for completing the project within scheduled time. TBM productivity largely depends on subsurface conditions and therefore, a prior understanding of the geological conditions is a crucial activity before start of tunnel excavation. The colaba – vidhan bhavan tunnel stretch of Mumbai metro line-3 planned to be excavated using single shield TBM as it yields minimal surface intervention however the major challenge lies on its close proximity to sea. This paper presents a case study of tunnel section where the alignment was passed mere 15–20 m off the coast of Arabian Sea. It was attempted to infer the ground well before actual TBM drive and adopted suitable ground improvement technique to mitigate and minimize the risk of pressurized flow of water flooding the tunnel.

A mineral project possesses important processing routes as it moves from discovery to technical and maintenance of the exploration and exploitation costs. The central thesis of studies in exploration is to increase the drilling optimization facilitating the selection of equipment and technology used to achieve highest drilling rate. A comprehensive survey of literature for prefeasibility stage of projects is presented to provide reliable and quantifiable options. The review classifies literature on exploratory coring rate into multiple classes and sub classes and identifies the nature of smart, connected systems offering new inter-operability in system of drilling processes. The research and development in this arena is resulting is focused on increasing the coring rate drilling efficiency without compromising safety and environment laws. A multi-disciplinary engineering approach in geophysics, sampling, weight on bit (WOB), machine selection, and flow rate (FR) on the rate of penetration (ROP) are the need of the hour to augment the ever increasing demand of mining industries.

Expansion of seaports often necessitates demolition of old berths near newly constructed berths. The 'Underwater drilling and blasting' technique is generally preferred for demolition due to higher economy and least dismantling time. The structural vibration in terms of Peak Particle Velocity (PPV) was to be limited below 75 mm/s for the structures located in the proximity as well as 508 mm/s for the connected concrete berth for preventing distress if any. Based on the scaling law established, a Hybrid Controlled Blasting (HCB) technique by redesigning the delays and charge quantities was established. The blast-induced radial crack was also estimated from stress theory to fix the distance between the pre-split hole and line drilling row as 1.5 m for an estimated charge per hole of 2.5 kg. One pre-split hole and two rows of 3 empty holes were drilled in a staggered pattern and blasted to detach the structure safely. The HCB technique helped in successfully screening the structural wave propagation and radial crack beyond the line-drilling row. The vibration progressively reduced from a predicted value of 87.59 mm/s to an actual value of 67.1 mm/s at the monitoring station. The structural strain was also controlled from 1925.4 mu mm/mm to less than crack initiation threshold of 1143 mu mm/mm at the nearest distance on the adjacent berth. The post-blast survey conducted confirmed that no crack was induced to adjacent berths proving the utility of the technique developed.

Land scarcity for infrastructure development and mining in developing nations such as India and Bhutan call for the adoption of effective underground space utilization techniques. Excavation rates, in tunnels from hydroelectric projects and development headings of underground mines implementing drill and blast methodology, need to be geared up to keep pace with the developmental requirements. Such excavations demand extensive drilling lengths, and realistic prediction of rock drillability is highly essential for determining the progress vis-à-vis feasibility of such excavation projects. Rock drillability investigations were taken up in this study covering a stretch of about 7 km of Indian Aravalli hills and Bhutan Himalayan mountains covering 15 rock variants. Prior research has indicated that several physico-mechanical properties of the rock play a crucial role in drillability assessment. Multilayer perceptron neural network indicated that quartz content (QC) and rock strength factor (RSF) predominantly influence penetration rates. A drillability prognosis model was developed that could explain the variance in laboratory penetration rate (LPR) up to 82.7% signifying a high level of correlation. Both QC and RSF were found to have negative relationships with LPR. It is inferred that the developed model is applicable for the rocks having quartz content varying from 30.0 to 96.0%, RSF from 35.8 to 74.0 MPa, and alternatively UCS and BTS values ranging from 65 to 142 MPa and 2.6 to 18.8 MPa, respectively. Correlations indicated that LPR could be a potential indicator of expected field penetration rate when there is little information about the rock mass parameters.

TBM tunneling in fractured rock masses in the vicinity of the sea is a major geological challenge, and such heterogeneous rock mass can lead to reduced productivity, a high risk of pressurized water inflow flooding the tunnel, and excessive ground movements leading to building damages in urban tunneling projects. A literature study was carried out to review the impact of difficult ground conditions on TBM tunneling. The presented work includes a case of the Mumbai Metro Line-3 UGC-01 project, a selected section where TBM alignment was passed mere 15 m off the coast of the Arabian Sea and this study is focused on ground characterization done to delineate the anomaly zones and further analyze the effect of difficult ground conditions on TBM operational and performance parameters in different weathering grades of basalt encountered near to sea section. Encountered ground conditions are divided into different zones based on the degree of fracturing in the rock mass, and further, all the TBM parameters are plotted to analyze the change in different zones. The paper also discusses the problems encountered during TBM excavation in each zone including high groundwater inflow and highly fractured rock mass. TBM operational and performance parameters which are analyzed include penetration per revolution, penetration speed, rate of penetration, weekly advance rates, cutter head rotation per minute, applied thrust force, and torque. The results highlight the effect of highly fractured rock masses, causing a significant reduction in TBM performance.

Dolomite, siliceous dolomite, phyllite, schist, leucogranite, pegmatite and gneissic rocks from the Indian Aravalli Hills and Bhutan Himalayan mountains were studied to examine the influence of petrographic and physico-mechanical properties on rock drillability.From petrographic assessments, a measure of grain size distribution, i.e. 'granularity index' and a 'modified saturation index' are proposed.Extensive rock mechanics and drilling experiments were also performed to correlate physico-mechanical properties with intact rock drillability.Statistical analysis revealed that no single petrographic parameter could completely explain the variance in drill penetration rate (DPR).The proposed indices and the petro-physico-mechanical approach helped in the rapid assessment of DPR in hard rocks.

Earth pressure balance tunnel boring machines (EPBTBM) are used in soft or mixed ground conditions often encountered in tunneling operations. The performance of EPBTBM could be enhanced to a great extent by appropriate time management, proper maintenance and reduced unproductive times such as idle hours and breakdown hours using reliability analysis. The reliability of a system primarily depends on time between failure (TBF) and maintainability is based on time to repair (TTR). Investigations on EPBTBM system performance were carried out for an irrigation tunnel through mixed strata conditions and the failure/repair data were collected. TBF and TTR data are found independent and identically distributed (IID). This implies that data are not following any particular trend or correlation. Therefore, these data are fitted in different types of probability distributions such as Gamma, Lognormal, Weibull with Easyfit and MATLAB tools. All the distributions are subjected to a Kolmogorov-Smirnov (k-s) test. Data analysis carried out on EPBTBM deployed in tunnels showed that TBF data and TTR data are found to best fit in General Gamma (4p) and General Gamma distribution respectively. Analysis indicated that ninety percent level of reliability of the system is at 2.64 h of operation whereas the mean time to repair is 5.78 h. The overall availability of the system was 67% which is comparatively less. Failure mode effects and criticality analysis (FMECA) was also carried out to find the critical part of the EPBTBM system. Disc cutter got the highest risk priority number indicating that it is the most vulnerable part of the EPBTBM. This paper reports that the availability of such systems can be increased to 80 percent by appropriate scheduling, preventive maintenance, and effective use of skilled manpower.

Traditional techniques of production blasting and delay timing patterns are restructured to minimise ground vibrations for the geological setting of Jharia coal field, a prime coking coal belt with densely covered habitat. Blasting techniques based on delay pattern and bench face orientation are proposed in this paper to protect the structures within a distance of 100 m from active bench face while maintaining daily production and charge per delay. Seventeen single representative blast holes (signature waveforms) were detonated in the last hole at the series of production blasts. When blast vibration was monitored in the opposite direction of the firing sequence and compared to the values in the same direction and behind the bench face, it was observed that the PPVs were less than 10 mm/s at 55 m radial distance. Also, when blast monitoring is setup near structures, across the strike of rock bed, blasting range can be designed 65 m away from structures rather than along the strike. The signature hole waveforms were generated using electronic delay detonators, and PPV values were controlled by maintaining delay intervals of 25 ms and 67 ms between holes and rows, respectively. Monte Carlo simulation (MCS) was used to generate the probabilistic data, and 5000 simulations helped to evaluate the volatility arising in the investigated blasting techniques, and it was concluded that the modified bench face design technique in 80 % of the cases generates PPV which is lower than the threshold value of 10 mm/s. The contribution to variance (CTV) and correlation coefficient (CC) approaches were used for the sensitivity analysis and it was observed that the bedding plane strike direction and radial distance are the two most critical factors impacting PPV. The proposed equation has shown high coefficient of determination (R-2 = 0.85) and low root mean square error (RMSE = 4.42) as compared to other four standard equations. Suggested blasting techniques can be of immense use for conducting production blasting in a safe and productive manner.

Fragment size optimization with selection of best values of blast design variables is an important process in mine-mill fragmentation system to maximize the system performance. This calls for measurement and analysis of mean fragment size with respect to blast design parameters. Digital image analysis technique is the most accepted method for measurement of blasted fragment sizes and their distribution. For quick assessment of the fragment sizes, a new novel method based on the digital images extracted from a blast video is reported in this paper. Correction factor for the size of fragments, considering the face movement is also proposed. The method has been tested with the help of seven blast data sets. The proposed dynamic image analysis technique can not only be used in fragment size estimation but also to assess the time-progressive size reduction in a blast, which can help designing the delay timing. Further, a possibility to estimate the in-situ block size is also explored with this method. The images of blast fragmentation were extracted from their videos at an interval of 0.08 s. These images were analyzed later for measurement of mean fragment size at respective times. The fragment size of the complete muck generated by the blast was also measured and correlated well with the sizes achieved from video analysis. The analysis revealed that from 0.08 s to 0.56 s from the initiation of the blasts, the fragment size reduction progressed from 58% to 80% of the estimated in-situ rock block sizes. Significant effect of blast design variables and two firing patterns on the mean fragment size was also observed. The analysis suggested that V-type firing pattern provides finer fragment size in comparison to the diagonal firing pattern. The suggested method provides an easy yet fast way for the assessment of blast fragment size.

Overburden removal is a major activity of surface coal mining and accounts for over 60–70% of the costs. Cast blasting is integral to overburden removal using draglines. Knowledge of cast blasting was combined with data analytics and machine learning algorithms to predict cast blast percentage. In a typical study, the cast percentage is predicted as a function of key input variables, namely (1) height to burden (H/b) ratio, (2) height to width (H/W) ratio, (3) length to width (L/W) ratio, (4) effective in-hole explosive density (de – te/m3), (5) powder factor (PF) (m3/kg – volume of rock broken per kg of explosive), and (6) average delay per unit width of burden (ms/m). Random forest algorithm was used under five-fold cross-validation with 68 datasets split into 57 for training and 11 for testing purposes. The model produced an R2 value of 69.16% and 67.37% respectively on the training and testing data.