Whole body vibration exposure and its effects on heavy earthmoving machinery (HEMM) operators of opencast mines – a review


Abstract : Operators of opencast heavy earthmoving machinery (HEMM), during their 8-hour shift duration, are regularly succumbed to the high level of whole body vibration (WBV) amplitudes. Due to long and continuous working in the field, the operators of HEMM may yield to adverse health effects and results in hazardous conditions if the magnitudes repeatedly exceed the permissible limits. Based on extensive literature review, the authors of the paper put forward the recognized harmful adverse health effect of short and longterm WBV exposure of HEMM operators in surface mining and also with the same view with the findings of various researchers in this field and feels that for the safety of operators, long-term understanding of WBV should be carried out instead of short term vibration monitoring.

Keywords: Whole body vibration (WBV), heavy earthmoving machinery (HEMM), low back pain (LBP), health guidance caution zone (HGCZ), root mean square (RMS)

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Optimal control of induction machines under minimum energy in opencast mining machinery

1 Jul 2020 / by AVEEK MANGAL

Abstract: Mining industry is one of the most important users of electric motors. The most commonly used in the contemporary mining industry is alternating current (AC) machines which are used for converting electrical energy into mechanical energy. This paper presents the solution of the nonlinear optimal control problems of three-phase induction mining machinery (IMM). A fifth order nonlinear model has been described in arbitrary rotating frame (d-q) of induction machine which is used in this paper along with a quadratic performance index (QPI). The problem has solved using the Taylor expansion about an operating point method which converts the nonlinear optimal control problem into sequence of linear quadratic optimal control problems. The control objective is to minimize the total energy, ensuring torque and speed tracking control requirements. The evaluation of a simulation for an electrical drive application shows that operation at varying optimal supply voltages (Vdsopt, Vqsopt) preserves well speed, torque and flux tracking performances, while increasing motor efficiency. The system is stable with the properly selected settings of optimal regulators, which are particularly applicable during the operation of machinery used in mining exploitations.

Keywords: Mining industry, induction motors, minimization of energy, Riccati equations, torque and speed control.

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Experimental studies for assessing spontaneous combustion risk of some Indian coals

1 Jul 2020 / by ARJUN KUMAR, D.P. TRIPATHY

Abstract: The self-heating or the spontaneous combustion of coal is processed by which the freshly exposed coal at ordinary atmospheric temperature when is exposed to oxygen undergo self-heating i.e. increase in its temperature and ultimately leading to auto ignition and mine fire. This spontaneous combustion leads to mine fires and are prime concern in the mining industry and let to huge coal loss and mine disaster. For safe coal mining, transportation, storage and uses, understanding the coal liability towards spontaneous combustion is important. Spontaneous heating liability depends upon the intrinsic as well as the extrinsic properties of the coal. In the present work, the spontaneous combustion susceptibility of a number of coal samples belonging to two different coalfields e.g.Bharat Coking Coal Limited (BCCL) and Central Coalfields Limited (CCL) of Coal India Limited, have been studied and its correlation with different intrinsic properties have been made. The objectives of this study is to assess the spontaneous heating liability of coal samples using differential thermal analysis and crossing point temperature and to establish a relationship between the spontaneous heating liability risk and intrinsic properties of coal samples. For this study, seven coal samples were collected from BCCL and CCL. Proximate analysis, bomb calorimetry, crossing point temperature (CPT) and differential thermal analysis (DTA), experiments were conducted to find the intrinsic properties of coals and assess their liability towards spontaneous heating. The paper summarizes the liability of different coal samples to spontaneous heating based on experiments conducted as well as broadly classifies the coal samples into poorly, moderately and highly susceptible to spontaneous heating risk. The transition temperature (Tc) indicated a very accurate measure of liability to spontaneous heating as they show high correlation coefficients with volatile matter, moisture and fixed carbon. These were 0.88% with moisture, 0.84% with volatile matter and 0.74 for fixed carbon contents. Lower the transition temperature of coal is higher will be the liability of coals to spontaneous heating. It was also observed that DTA study was found to give better correlation and hence, it may be used for assessment of spontaneous heating susceptibility of coal. It was observed that the coal samples containing high moisture are in general more liable to spontaneous heating. Spontaneous heating also shows a direct relationship with volatile matter hence higher the volatile matter in the coal samples is more will be the liability towards spontaneous heating. Ash percentage also has negative slope [-1.87] with transition temperature but the correlation coefficient is very low [0.15]. It has also lowest correlation coefficient (0.10) values with CPT. Gross calorific value is also directly dependent on the fixed carbon. Coal samples having higher fixed carbon are less liable for spontaneous heating. Ash has very low correlation coefficients with CPT and transition temperature and hence is not helpful in the assessment of liability towards spontaneous heating and it is of least importance.

Keywords: Spontaneous combustion, Indian coal, proximate analysis, transition temperature, crossing point temperature (CPT), ifferential thermal analysis (DTA)

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Effect of cracks on the stability of dump slope


Abstract: Maintaining the stability of overburden dumps in opencast mines is a major challenge. Instability in dump slope occurs because of many inherent factors, cracks formed by mining activities, and natural climatic conditions etc. have been considered in this study. Numerical simulation of the dump slope has been performed using RS2 (Rocscience) software based on the finite element method (FEM). In simulation, the effect of cracks by considering the crack inclination, crack location from the crest of the dump slope, and effect of crack length and crack inclination at critical failure surface location has been analyzed. It has been found for the given conditions that cracks at a distance less than 7.5m from the crest of the slope for inclination 30° to 50° have the least stability and crack at critical failure surface location for inclination 40°, and 50° have a significant effect on the stability of the dump slope for all the considered crack length.

Keyword: Dump slope, crack, finite element method, numerical modeling.

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Performance study for diesel engine: a single cylinder using a new electronic control unit of (diesel+liquefied petroleum gas) mode


Diesel engines are important and effective in many services, but it is no friendly for environmentally. Since liquefied petroleum gas is prolific in Iraq at a lower price than other fuels and is clean and environmentally friendly, one of the important research topics is the use of liquefied petroleum gas in diesel engines because LPG has a high heat value, and the state of its gas makes mixing with air a burning issue simple and improved, reduces emissions and helps to harvest total energy. A new electronic control unit (ECU) is designed and used to inject liquefied petroleum gas via intake manifold as air enters the combustion chamber and a sensor is installed over a single-cylinder diesel engine, air-cooling. The test engine operation for fuel modes that were initially used is the D- 100, after which the LPG-25, LPG-50 and LPG-100 fuel were used. The test under loads was 0%, 25%, 50%, 75% and 100% at different speeds of 1000, 1500 and 2000 rpm. At engine speeds, 1000, 1500, 2000 rpm compared to D- 100 fuel, thermal efficiency was better in using LPG-50 fuel and improved by (4%, 3.6%, 4.9 %), and bsfc (9.81%, 9.4% and 9.68%) respectively, A decrease in emissions, NO x , HC, CO and CO 2 was observed in all operating modes with liquefied petroleum gas and the best emission reduction situation is LPG -50.

Keywords: Dual fuel, diesel engine, liquefied petroleum gas, emissions.

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Long-term open pit mine production scheduling with variable cut off grade for cost optimization


Selection of cut off grade in long-term open pit mine planning is a tough research challenge now-a-days. The subsequent operational planning for the selected cut off grade decides the economic factor in mine production
scheduling. The distribution of grade, sequence of mining operation, economic parameters, the capacities of mining operations are influencing points for deciding the model. In any given period of time the dynamic cut off grade is a
function of the availability of ore and the capacity of stockpile as well as the process plant. The extraction sequence and cut off grade strategy should be considered simultaneously in order to achieve the optimum result. By keeping these points in first row, various attempts have been made to develop an electronic technique for the extraction sequence of open pit mines. Because of the numerous variables involved for getting the optimum result, different approaches have been made is not sufficient to widespread acceptance. A new model has therefore been proposed to overcome this shortcoming. The optimum sequences of extraction in each period are recognized by optimum processing decisions. To examine the applicability of the model developed, a case study is offered to validate.

Keywords: NPV, production scheduling, economic loss, mining sequence, cut off grade

1. Akaike, A., and Dagdelen, K. (1999): A strategic production scheduling method for an open pit mine. Proceedings of the
28th Application of Computers and Operation Research in the Mineral Industry, 729-738.
2. Asad, M. W. A. (2002): Development of generalized cutoff grade optimization algorithm for open pit mining
operations. Journal of Engineering and Applied Sciences, 21(2).
3. Ataei, M., and Osanloo, M. (2003): Methods for calculation of optimal cutoff grades in complex ore deposits. Journal of
Mining Science, 39(5), 499-507.
4. Ataei, M., and Osanloo, M. (2004): Using a combination of genetic algorithm and the grid search method to determine
optimum cutoff grades of multiple metal deposits. International Journal of Surface Mining, Reclamation and Environment,
18(1), 60-78.
5. Boland, N., Dumitrescu, I., Froyland, G., and Gleixner, A. M. (2009): LP-based disaggregation approaches to solving the open
pit mining production scheduling problem with block processing selectivity. Computers & Operations Research, 36(4), 1064-
1089.6. Cairns, R. D., and Shinkuma, T. (2003): The choice of the cutoff grade in mining. Resources Policy, 29(3-4), 75-81.
7. Dagdelen, K. (1985): Optimum multi-period open pit mine production scheduling. PhD thesis, Colorado School of
Mines, Golden, Colorado.
8. Dagdelen, K. (1986): Optimum open pit mine production scheduling by Lagrangian parameterization. Proc. of the 19
APCOM, 127-142.
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Computers and Operations Research in Minerals Industries (pp. 257-263).
11. Gershon, M. E. (1983): Optimal mine production scheduling: evaluation of large-scale mathematical
programming approaches. International Journal of Mining Engineering, 1(4), 315-329.
12. Gholamnejad, J. (2009): Incorporation of rehabilitation cost into the optimum cut-off grade determination. Journal of the
Southern African Institute of Mining and Metallurgy, 109(2), 89-94.
13. Gleixner, A. M. (2009): Solving large-scale open pit mining production scheduling problems by integer programming.
14. Halls, J. L., Bellum, D. P., and Lewis, C. K. (1969): Determination of optimum ore reserves and plant size by incremental
financial analysis. Transactions of the Institute of Mining and Metallurgy, 78, A20-A26.
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Revised 4-D Network Relaxation Method. Journal-mining and materials processing institute of Japan, 117(7), 599-603.

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Failure mode, effects and criticality analysis of dragline components and evaluation of risk priority number for effective maintenance planning


The occurrences of unexpected failures in heavy earthmoving machines (HEMMs) lead to the downtime
that reduces the productivity, safety, and reliability of the machines. Unwanted failures increase the likelihood of
unplanned maintenance activities. Dragline is an HEMM used in the opencast coal mines for removal of the
overburden and its failure is undesirable as the capital invested on draglines are very high. This paper utilises the
failure mode, effects and criticality analysis (FMECA) to identify the critical failure components of the dragline
system and their root causes. Seven subsystems and thirty components for failure have been identified in the two-
year maintenance record 2014-16 of dragline. Risk estimation has been carried out for the dragline components to
estimate the risk priority number (RPN) considering four factors: failure occurrence, production loss, degradation in
performance, and detectability. The RPN is used to categorise the components into three groups: high, medium, and
low risk components. Based on the risk groups of component, the inspection interval and inspection time can be
optimised to avoid the unexpected failure of the component and eventually improving the productivity of the
dragline system.

Keywords: Dragline; FMECA; risk priority number; maintenance; HEMM

1. Adar, E., Ince, M., Karatop, B., and Bilgili, M. S. (2017): The risk analysis by failure mode and effect analysis (FMEA) and
fuzzy-FMEA of supercritical water gasification system used in the sewage sludge treatment. Journal of Environmental Chemical
Engineering, 5(1), 1261–1268. https://doi.org/ 10.1016/j.jece.2017.02.006
2. Arabian-Hoseynabadi, H., Oraee, H., and Tavner, P. J. (2010): Failure Modes and Effects Analysis (FMEA) for wind turbines.
International Journal of Electrical Power and Energy Systems, 32(7), 817–824. https://doi.org/10.1016/j.ijepes. 2010.01.019
3. Arunraj, N. S. and Maiti, J. (2007): Risk-based maintenance- Techniques and applications. Journal of Hazardous Materials,
142(3), 653–661. https://doi.org/10.1016/j.jhazmat. 2006.06.069
4. Balaraju, J., Govinda Raj, M., and Murthy, C. S. (2019): Fuzzy-FMEA risk evaluation approach for LHD machine-A case
study. Journal of Sustainable Mining, 18(4), 257–268. https://doi.org/10.1016/j.jsm.2019.08.002
5. Carmignani, G. (2009): An integrated structural framework to cost-based FMECA: The priority-cost FMECA. Reliability
Engineering and System Safety, 94(4), 861–871. https://doi.org/10.1016/j.ress.2008.09.009
6. Chang, C. L., Liu, P. H., and Wei, C. C. (2001): Failure mode and effects analysis using grey theory. Integrated Manufacturing
Systems, 12(3), 211–216. https://doi.org/ 10.1108/095760601103911747. Chang, W. L., Pang, L. M. and Tay, K. M. (2017): Application of self-organizing map to failure modes and effects analysis
methodology. Neurocomputing, 249, 314–320. https://doi.org/10.1016/j.neucom.2016.04.073
8. Chen, K. S., Wang, C. C., Wang, C. H. and Huang, C. F. (2010): Application of RPN analysis to parameter optimization of
passive components. Microelectronics Reliability, 50(12), 2012–2019. https://doi.org/10.1016/j.microrel.2010.06.014
9. Demirel, N.and Golbasi, O. (2016): Preventive Replacement Decisions for Dragline Components Using Reliability
Analysis. Minerals, 6(2), 51. https://doi.org/10.3390/min6020051
10. Feili, H. R., Akar, N., Lotfizadeh, H., Bairampour, M. and Nasiri, S. (2013): Risk analysis of geothermal power plants using
Failure Modes and Effects Analysis (FMEA) technique. Energy Conversion and Management, 72, 69–76.
11. Golbasi, O. and Demirel, N. (2017): A cost-effective simulation algorithm for inspection interval optimization: An
application to mining equipment. Computers and Industrial Engineering, 113, 525–540. https://doi.org/10.1016/j.cie.2017.09.002
12. Golbas1, O. and Demirel, N. (2017): Optimisation of dragline inspection intervals with time-counter algorithm.
International Journal of Mining, Reclamation and Environment, 31(6), 412–425. https://doi.org/10.1080/17480930.2017.1339168
13. Helvacioglu, S. and Ozen, E. (2014): Fuzzy based failure modes and effect analysis for yacht system design. Ocean
Engineering, 79, 131–141. https://doi.org/10.1016/j.oceaneng.2013.12.015
14. Kim, K. O. and Zuo, M. J. (2018): General model for the risk priority number in failure mode and effects analysis. Reliability
Engineering and System Safety, 169, 321–329. https://doi.org/ 10.1016/j.ress.2017.09.010
15. Li, Y. and Liu, W. (2013): Dynamic dragline modeling for operation performance simulation and fatigue life prediction.
Engineering Failure Analysis, 34, 93–101. https://doi.org/10.1016/j.engfailanal.2013.07.020
16. Lo, H.-W. and Liou, J. J. H. (2018): A novel multiple-criteria decision-making-based FMEA model for risk assessment.
Applied Soft Computing Journal, 73, 684–696. https://doi.org/ 10.1016/j.asoc.2018.09.020
17. Lo, H. W., Liou, J. J. H., Huang, C. N. and Chuang, Y. C. (2019): A novel failure mode and effect analysis model for
machine tool risk analysis. Reliability Engineering and System Safety, 183, 173–183. https://doi.org/10.1016/j.ress.2018.11.018
18. Mzougui, I. and Felsoufi, Z. El. (2019): Proposition of a modified FMEA to improve reliability of product. Procedia
CIRP, 84, 1003–1009. https://doi.org/10.1016/ j.procir.2019.04.315
19. Passath, T. and Mertens, K. (2019): Decision Making in Learn Smart Maintenance/ : Criticality Analysis as a Support Tool.
IFAC-PapersOnLine, 52(10), 364–369. https://doi.org/10.1016/j.ifacol.2019.10.058
20. Ponnusamy, M. and Maity, T. (2016): Recent advancements in Dragline control systems. Journal of Mining Science, 52(1),
160–168. https://doi.org/10.1134/S106273911601025X
21. Rai, P., Yadav, U. and Kumar, A. (2011): Productivity Analysis of Draglines Operating in Horizontal and Vertical Tandem
Mode of Operation in a Coal Mine-A Case Study. Geotechnical and Geological Engineering, 29(4), 493–504.
22. Rajput, P., Malvoni, M., Kumar, N. M. and Tiwari, G. N. (2019): Risk priority number for understanding the severity of
photovoltaic failure modes and their impacts on performance degradation. Case Studies in Thermal Engineering, 16, 100563.
23. Renjith, V. R., Jose kalathil, M., Kumar, P. H. and Madhavan, D. (2018): Fuzzy FMECA (failure mode effect and criticality
analysis) of LNG storage facility. Journal of Loss Prevention in the Process Industries, 56, 537–547.
24. Renu, R., Visotsky, D., Knackstedt, S., Mocko, G., Summers, J. D. and Schulte, J. (2016). A Knowledge Based FMEA to
Support Identification and Management of Vehicle Flexible Component Issues. Procedia CIRP, 44, 157–162.
25. Scheu, M. N., Tremps, L., Smolka, U., Kolios, A. and Brennan, F. (2019): A systematic Failure Mode Effects and Criticality
Analysis for offshore wind turbine systems towards integrated condition based maintenance strategies. Ocean Engineering,
176, 118–133. https://doi.org/10.1016/j.oceaneng.2019.02.04826. Sharma, R. K., Kumar, D. and Kumar, P. (2005): Systematic failure mode effect analysis (FMEA) using fuzzy linguistic

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Critical analysis of Indian soda lime: scope of Improvement


Soda lime is one of the most popular carbon dioxide absorbent materials to be used for closed-circuit life saving safety breathing apparatus in mining industries. A trained rescue person uses it during a situation such as a
fire, explosion or emission of toxic gasses in underground mines. This paper evaluates the chemical composition and physical properties of soda lime using specific parameters (moisture, carbon dioxide gas absorption, granule shape and fine particle size) which plays an important role in its application in breathing apparatus. Results indicated that soda lime moisture content, fine grains and hardness ranged between 11.6-18.3%, 0.2-1.9g, and 70-90%,
respectively. The CO 2 absorption rate was observed to be 20.0 to 57.0 minutes compared to standard UK Protosorb soda lime CO 2 (135 minutes). X-Ray Diffraction (XRD), Energy Dispersive Spectroscopy (EDS) and Scanning
Electron Microscope (SEM) analysis of the samples were carried out to understand the changes in molecular structure of the material before and after CO 2 absorption. The XRD result indicated presence of portlandite
(48.5%),calcite (49.6%) and potassium rhenium sulfide telluride cyan acetate (PRSTCA) (1.84%) before CO 2 absorption and calcite calcium carbonate (89.4%) portlandite (3.38%) and octasodium d-potassium tetra hydrogen
dihydroxo tetra telluride dipalladate (7.2%), 20-hydrate was observed after CO 2 absorption. EDS of sample 6 indicated presence of carbon (4.94%), oxygen (39.80%) sodium (3.36%) and calcium (51.90%) before CO 2 absorption and carbon (6.27%), oxygen (36 96%), sodium (1.37%) and calcium (55.40%) after CO 2 absorption.

Keywords: Carbon dioxide (CO 2 ), soda lime, hot air oven, breathing apparatus, XRD, EDS, SEM.

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