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Development of an evaluation system for blasting patterns to provide efficient production

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Abstract

Blasting is one of the most important operations in mining projects involving production. Inappropriate blasting pattern may lead to unwanted events such as poor fragmentation, back break, fly rock, etc., as well as strong effects on the production rate. In fact, the selection of the most suitable pattern among the previously performed patterns can be considered as a Multi Attribute Decision Making problem. In this paper, first, from various performed patterns, the efficient and inefficient ones were determined using Data Envelopment Analysis. In the second step, linear assignment was used to evaluate the efficient patterns and recognize the most suitable pattern for providing high production rate. According to the obtained results, blasting pattern with the burden of 3.5 m, the spacing of 4.5 m, the stemming of 3.8 m and the hole length of 12.1 m was selected as the most appropriate blasting pattern and suggested for the future blasting operations.

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References

  • Ak, H., Iphar, M., Yavuz, M., & Konuk, A. (2009). Evaluation of ground vibration effect of blasting operations in a magnesite mine. Soil Dynamics and Earthquake Engineering, 29(4), 669–676.

    Article  Google Scholar 

  • Ak, H., & Konuk, A. (2008). The effect of discontinuity frequency on ground vibrations produced from bench blasting: A case study. Soil Dynamics and Earthquake Engineering, 28(9), 686–694.

    Article  Google Scholar 

  • Al-Refaie, A., & Al-Tahat, M. D. (2011). Solving the multi-response problem in Taguchi method by benevolent formulation in DEA. Journal of Intelligent Manufacturing, 22(4), 505–521.

    Article  Google Scholar 

  • Allen, R., & Thanassoulis, E. (2004). Improving envelopment in data envelopment analysis. European Journal of Operational Research, 154(2), 363–379.

    Article  Google Scholar 

  • Amini, H., Gholami, R., Monjezi, M., Torabi, S. R., & Zadhesh, J. (2011). Evaluation of flyrock phenomenon due to blasting operation by support vector machine. Neural Computing and Applications, 1–9.

  • Athanassopoulos, A. D., Lambroukos, N., & Seiford, L. (1999). Data envelopment scenario analysis for setting targets to electricity generating plants. European Journal of Operational Research, 115(3), 413–428.

    Article  Google Scholar 

  • Azadeh, A., Osanloo, M., & Ataei, M. (2010). A new approach to mining method selection based on modifying the Nicholas technique. Applied Soft Computing, 10(4), 1040–1061.

  • Bajpayee, T., Bhatt, S. K., Rehak, T. R., Engineer, G., Mowrey, G. L., & Ingram, D. K. (2003). Fatal accidents due to flyrock and lack of blast area security and working practices in mining. Journal of Mines, Metals and Fuels, 51(11–12), 344–349.

    Google Scholar 

  • Bajpayee, T., Rehak, T., Mowrey, G., & Ingram, D. A. (2002). Summary of fatal accidents due to flyrock and lack of blast area security in surface mining, 1989 to 1999. In Proceedings of the annual of the conference on explosives and blasting technique, (Vol. 2, pp. 105–118): ISEE 1999.

  • Bajpayee, T., Rehak, T., Mowrey, G., & Ingram, D. (2004). Blasting injuries in surface mining with emphasis on flyrock and blast area security. Journal of Safety Research, 35(1), 47–57.

    Article  Google Scholar 

  • Bajpayee, T., Verakis, H., & Lobb, T. (2004). An analysis and prevention of flyrock accidents in surface blasting operations. In Proceedings of the annual of the conference on explosives and blasting technique, (Vol. 2, pp. 401–410): ISEE; 1999.

  • Bakhshandeh Amnieh, H., Siamaki, A., & Soltani, S. (2012). Design of blasting pattern in proportion to the peak particle velocity (PPV): Artificial neural networks approach. Safety Science, 50(9), 1913–1916.

    Article  Google Scholar 

  • Bal, H., Örkcü, H. H., & Çelebioğlu, S. (2010). Improving the discrimination power and weights dispersion in the data envelopment analysis. Computers and Operations Research, 37(1), 99–107.

    Article  Google Scholar 

  • Bazzazi, A. A., Osanloo, M., & Karimi, B. (2011). A new fuuzzy multi criteria decision making model for open pit mines equipment selection. Asia-Pacific Journal of Operational Research, 28(03), 279–300.

    Article  Google Scholar 

  • Bazzazi, A. A., Osanloo, M., & Soltanmohammadi, H. (2008). Loading-haulage equipment selection in open pit mines based on fuzzy-TOPSIS method. Gospodarka Surowcami Mineralnymi, 24.

  • Bejari, H., Shahriar, K., Hamidi, J. K., & Shirazi, M. A. (2010). Optimal tunneling method selection using fuzzy multiple attribute decision making technique. In ISRM International symposium-6th Asian rock mechanics symposium.

  • Chakraborty, A., Raina, A., Ramulu, M., Choudhury, P., Haldar, A., Sahu, P., et al. (2004). Parametric study to develop guidelines for blast fragmentation improvement in jointed and massive formations. Engineering Geology, 73(1), 105–116.

    Article  Google Scholar 

  • Cho, S. H., & Kaneko, K. (2004). Rock fragmentation control in blasting. Materials Transactions, 45(5), 1722–1730.

    Article  Google Scholar 

  • Chu, M.-T., Shyu, J. Z., & Khosla, R. (2008). Measuring the relative performance for leading fabless firms by using data envelopment analysis. Journal of Intelligent Manufacturing, 19(3), 257–272.

    Article  Google Scholar 

  • Cooper, W. W., Seiford, L. M., & Tone, K. (2005). Introduction to data envelopment analysis and its uses: With DEA-solver software and references.

  • Cooper, W. W., Seiford, L. M., & Tone, K. (2007). Data envelopment analysis: A comprehensive text with models, applications, references and DEA-solver software. Berlin: Springer.

    Google Scholar 

  • Crum, S., & Crum, S. (1990). Fractal concepts applied to bench-blast fragmentation. Rock Mechanics Contributions and Challenges: Proc. 919.

    Google Scholar 

  • Dağdeviren, M. (2008). Decision making in equipment selection: An integrated approach with AHP and PROMETHEE. Journal of Intelligent Manufacturing, 19(4), 397–406.

    Article  Google Scholar 

  • Dehghani, H., & Ataee-Pour, M. (2011). Development of a model to predict peak particle velocity in a blasting operation. International Journal of Rock Mechanics and Mining Sciences, 48(1), 51–58.

    Article  Google Scholar 

  • Erarslan, K., Uysal, Ö., Arpaz, E., & Cebi, M. A. (2008). Barrier holes and trench application to reduce blast induced vibration in Seyitomer coal mine. Environmental Geology, 54(6), 1325–1331.

  • Gate, W., Ortiz, B., & Florez, R. (2005). Analysis of rockfall and blasting backbreak problems. In Paper ARMA/USRMS, proceedings of the American rock mechanics conference, (Vol. 5, pp. 671–680).

  • Ghasemi, E., Amini, H., Ataei, M., & Khalokakaei, R. (2012a). Application of artificial intelligence techniques for predicting the flyrock distance caused by blasting operation. Arabian Journal of Geosciences, 1–10.

  • Ghasemi, E., Sari, M., & Ataei, M. (2012b). Development of an empirical model for predicting the effects of controllable blasting parameters on flyrock distance in surface mines. International Journal of Rock Mechanics and Mining Sciences, 52, 163–170.

    Article  Google Scholar 

  • Guoliang, Z., & Sijing, C. (2010). The application of fuzzy comprehensive evaluation and topsis approach to selection of optimum underground mining method. In information science and engineering (ICISE), 2010 2nd international conference on, 2010 (pp. 6233–6237): IEEE.

  • Guosheng, Z., Jiang, L., & Kui, Z. (2011). Structural safety criteria for blasting vibration based on wavelet packet energy spectra. Mining Science and Technology (China), 21(1), 35–40.

    Article  Google Scholar 

  • Hekmat, A., Osanloo, M., & Shirazi, A. (2008). New approach for selection of waste dump sites in open pit mines. Mining Technology, 117(1), 24–31.

    Article  Google Scholar 

  • Hermans, E., Brijs, T., Wets, G., & Vanhoof, K. (2009). Benchmarking road safety: Lessons to learn from a data envelopment analysis. Accident Analysis and Prevention, 41(1), 174–182.

    Article  Google Scholar 

  • Hudaverdi, T. (2012). Application of multivariate analysis for prediction of blast-induced ground vibrations. Soil Dynamics and Earthquake Engineering, 43, 300–308.

    Article  Google Scholar 

  • Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications: A state-of-the-art survey (Vol. 13). New York: Springer-Verlag.

    Book  Google Scholar 

  • Inanloo Arabi Shad, H., & Ahangari, K. (2012). An empirical relation to calculate the proper burden in blast design of open pit mines based on modification of the Konya relation. International Journal of Rock Mechanics and Mining Sciences, 56, 121–126.

    Article  Google Scholar 

  • Iphar, M., Yavuz, M., & Ak, H. (2008). Prediction of ground vibrations resulting from the blasting operations in an open-pit mine by adaptive neuro-fuzzy inference system. Environmental Geology, 56(1), 97–107.

  • Jimeno, C. (1995). Rock drilling and blasting. Rotterdam, Brookfield: AA Balkema.

    Google Scholar 

  • Kao, C., & Liu, S.-T. (2009). Stochastic data envelopment analysis in measuring the efficiency of Taiwan commercial banks. European Journal of Operational Research, 196(1), 312–322.

    Article  Google Scholar 

  • Kecojevic, V., & Radomsky, M. (2005). Flyrock phenomena and area security in blasting-related accidents. Safety Science, 43(9), 739–750.

    Article  Google Scholar 

  • Khandelwal, M., & Monjezi, M. (2012). Prediction of backbreak in open-pit blasting operations using the machine learning method. Rock Mechanics and Rock Engineering, 1–8.

  • Kulatilake, P., Qiong, W., Hudaverdi, T., & Kuzu, C. (2010). Mean particle size prediction in rock blast fragmentation using neural networks. Engineering Geology, 114(3), 298–311.

    Article  Google Scholar 

  • Lashgari, A., Fouladgar, M. M., Yazdani-Chamzini, A., & Skibniewski, M. J. (2011). Using an integrated model for shaft sinking method selection. Journal of Civil Engineering and Management, 17(4), 569–580.

    Article  Google Scholar 

  • Lashgari, A., Yazdani-Chamzini, A., Fouladgar, M. M., Zavadskas, E. K., Shafiee, S., & Abbate, N. (2012). Equipment selection using fuzzy multi criteria decision making model: Key study of gole gohar iron min. Engineering Economics, 23(2), 125–136.

    Article  Google Scholar 

  • Lashgari, A., Yazdani, A., & Sayadi, A. (2010). Methods for equipments selection in surface mining; review.

  • Latham, J.-P., Van Meulen, J., & Dupray, S. (2006). Prediction of fragmentation and yield curves with reference to armourstone production. Engineering Geology, 87(1), 60–74.

    Article  Google Scholar 

  • Li, S., Jahanshahloo, G. R., & Khodabakhshi, M. (2007). A super-efficiency model for ranking efficient units in data envelopment analysis. Applied Mathematics and Computation, 184(2), 638–648.

    Article  Google Scholar 

  • Little, T., & Blair, D. (2010). Mechanistic Monte Carlo models for analysis of flyrock risk. Rock Fragmentation by Blasting, 641–647.

  • Michaux, S., & Djordjevic, N. (2005). Influence of explosive energy on the strength of the rock fragments and SAG mill throughput. Minerals Engineering, 18(4), 439–448.

    Article  Google Scholar 

  • Mikaeil, R., Naghadehi, M. Z., Ataei, M., & KhaloKakaie, R. (2009). A decision support system using fuzzy analytical hierarchy process (FAHP) and TOPSIS approaches for selection of the optimum underground mining method. Archives of Mining Sciences, 54(2), 341–368.

    Google Scholar 

  • Monjezi, M., Ahmadi, M., Sheikhan, M., Bahrami, A., & Salimi, A. (2010a). Predicting blast-induced ground vibration using various types of neural networks. Soil Dynamics and Earthquake Engineering, 30(11), 1233–1236.

    Article  Google Scholar 

  • Monjezi, M., Amini Khoshalan, H., & Yazdian Varjani, A. (2011a). Optimization of open pit blast parameters using genetic algorithm. International Journal of Rock Mechanics and Mining Sciences, 48(5), 864–869.

    Article  Google Scholar 

  • Monjezi, M., Amini Khoshalan, H., & Yazdian Varjani, A. (2012). Prediction of flyrock and backbreak in open pit blasting operation: A neuro-genetic approach. Arabian Journal of Geosciences, 5(3), 441.

    Article  Google Scholar 

  • Monjezi, M., Bahrami, A., Varjani, A. Y., & Sayadi, A. R. (2011b). Prediction and controlling of flyrock in blasting operation using artificial neural network. Arabian Journal of Geosciences, 4(3), 421–425.

    Article  Google Scholar 

  • Monjezi, M., & Dehghani, H. (2008). Evaluation of effect of blasting pattern parameters on back break using neural networks. International Journal of Rock Mechanics and Mining Sciences, 45(8), 1446–1453.

    Article  Google Scholar 

  • Monjezi, M., Ghafurikalajahi, M., & Bahrami, A. (2011c). Prediction of blast-induced ground vibration using artificial neural networks. Tunnelling and Underground Space Technology, 26(1), 46–50.

    Article  Google Scholar 

  • Monjezi, M., & Rezaei, M. (2011). Developing a new fuzzy model to predict burden from rock geomechanical properties. Expert Systems with Applications, 38(8), 9266–9273.

    Article  Google Scholar 

  • Monjezi, M., Rezaei, M., & Yazdian, A. (2010b). Prediction of backbreak in open-pit blasting using fuzzy set theory. Expert Systems with Applications, 37(3), 2637–2643.

    Article  Google Scholar 

  • Morin, M. A., & Ficarazzo, F. (2006). Monte Carlo simulation as a tool to predict blasting fragmentation based on the Kuz-Ram model. Computers and Geosciences, 32(3), 352–359.

    Article  Google Scholar 

  • Namin, F. S., Shahriar, K., Ataee-pour, M., & Dehghani, H. (2008). A new model for mining method selection of mineral deposit based on fuzzy decision making.

  • Ning, K. (1999). Prevention measures for controlling flyrock in engineering blasting [J]. Blasting.

  • Ozkahraman, H. (2006). Fragmentation assessment and design of blast pattern at Goltas Limestone Quarry, Turkey. International Journal of Rock Mechanics and Mining Sciences, 43(4), 628–633.

    Article  Google Scholar 

  • Rehak, T., Bajpayee, T., Mowrey, G., & Ingram, D. (2001). Flyrock issues in blasting. In proceedings of the annual conference on explosives and blasting technique, 2001 (Vol. 1, pp. 165–176): ISEE; 1999.

  • Rezaei, M., & Monjezi, M. (2011). Development of a fuzzy model to predict flyrock in surface mining. Safety Science, 49(2), 298–305.

  • Sanchidrián, J., Segarra, P., & López, L. (2006). A practical procedure for the measurement of fragmentation by blasting by image analysis. Rock Mechanics and Rock Engineering, 39(4), 359–382.

    Article  Google Scholar 

  • Sheikhalishahi, M., Ebrahimipour, V., & Farahani, M. H. (2013). An integrated GA-DEA algorithm for determining the most effective maintenance policy for ak-out-of-n problem. Journal of Intelligent Manufacturing, 1–8.

  • Shim, H.-J., Ryu, D.-W., Chung, S.-K., Synn, J.-H., & Song, J.-J. (2009). Optimized blasting design for large-scale quarrying based on a 3-D spatial distribution of rock factor. International Journal of Rock Mechanics and Mining Sciences, 46(2), 326–332.

    Article  Google Scholar 

  • Shuran, L., & Shujin, L. (2011). Applying BP Neural Network Model to Forecast Peak Velocity of Blasting Ground Vibration. Procedia Engineering, 26, 257–263.

    Article  Google Scholar 

  • Singh, T., & Singh, V. (2005). An intelligent approach to prediction and control ground vibration in mines. Geotechnical and Geological Engineering, 23(3), 249–262.

    Article  Google Scholar 

  • Sowlati, T., Paradi, J. C., & Suld, C. (2005). Information systems project prioritization using data envelopment analysis. Mathematical and Computer Modelling, 41(11), 1279–1298.

  • Stojadinović, S., Pantović, R., & Žikić, M. (2011). Prediction of flyrock trajectories for forensic applications using ballistic flight equations. International Journal of Rock Mechanics and Mining Sciences, 48(7), 1086–1094.

    Article  Google Scholar 

  • Tota, E. W., Mudge, K., Branson, J. W., Georgiou, P. N., Gavrilovic, M., & Watson, J. D. (2001). Method and apparatus for flyrock control in small charge blasting. Google Patents.

  • Wang, C.-H., & Wu, H.-S. (2014). A novel framework to evaluate programmable logic controllers: A fuzzy MCDM perspective. Journal of Intelligent Manufacturing, 1–10.

  • Yazdani-Chamzini, A., & Yakhchali, S. H. (2012). Handling equipment selection in open pit mines by using an integrated model based on group decision making. International Journal of Industrial Engineering, 3.

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  1. Department of Mining Engineering, Isfahan University of Technology, 8415683111, Isfahan, Iran

    Mojtaba Yari, Raheb Bagherpour & Saeed Jamali

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  1. Mojtaba Yari
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Yari, M., Bagherpour, R. & Jamali, S. Development of an evaluation system for blasting patterns to provide efficient production. J Intell Manuf 28, 975–984 (2017). https://doi.org/10.1007/s10845-015-1036-6

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