Selection of an Appropriate Method to Extract the Dimensional Stones Using FDAHP & TOPSIS Techniques

Document Type : Regular Article

Authors

1 Urmia University of Technology, Urmia, Iran

2 University of Birjand, Birjand, Iran

Abstract

In this paper, it was aimed to select a suitable method to extract the dimensional stone to increase dimensional stone quarries efficiency. The usual methods including diamond cutting-wire method, blasting method, plug, and feather method, Katrock expanding material and Fract expanding material have compared using TOPSIS (Technique for Order Performance by Similarity to Ideal Solution) method by respecting to the following criteria: grass income, safety, desirability, reduction of environmental impacts, waste and reduction of extracting time. FDAHP (Fuzzy Delphi Analytic Hierarchy Process) approach was used in determining the degree of importance of the criteria by expert decision makers. Also, those criteria performed the same impacts were not considered. Consequently, the diamond wire saw method was suggested as the most appropriate method to extract the dimensional stones. It was concluded that the extraction of dimensional stone using diamond wire saw is the best method based on the mentioned criterion compared to other methods.

Highlights

Google Scholar

Keywords

Main Subjects


[1]     Mikaiel R, Ataei MA, Hoseinie H. Predicting the production rate of diamond wire saws in carbonate rock cutting. Ind Diam Rev 2008;68:28–34.
[2]     Mikaeil R, Ataei M, Yousefi R. Application of a fuzzy analytical hierarchy process to the prediction of vibration during rock sawing. Min Sci Technol 2011;21:611–9. doi:10.1016/j.mstc.2011.03.008.
[3]     Mikaeil R, Yousefi R, Ataei M, Farani RA. Development of a new classification system for assessing of carbonate rock sawability. Arch Min Sci 2011;56:59–70.
[4]     Ataei M, Mikaiel R, Sereshki F, Ghaysari N. Predicting the production rate of diamond wire saw using statistical analysis. Arab J Geosci 2012;5:1289–95. doi:10.1007/s12517-010-0278-z.
[5]     Mikaeil R, Ataei M, Yousefi R. Correlation of production rate of ornamental stone with rock brittleness indexes. Arab J Geosci 2013;6:115–21. doi:10.1007/s12517-011-0311-x.
[6]     Mikaeil R, Yousefi R, Ataei M. Sawability ranking of carbonate rock using fuzzy analytical hierarchy process and TOPSIS approaches. Sci Iran 2011;18:1106–15. doi:10.1016/j.scient.2011.09.009.
[7]     Mikaeil R, Ataei M, Yousefi R. Evaluating the Power Consumption in Carbonate Rock Sawing Process by Using FDAHP and TOPSIS Techniques. Effic. Decis. Support Syst. Challenges Multidiscip. Domains, 2011.
[8]     Mikaeil R, Ozcelik Y, Ataei M, Yousefi R. Correlation of specific ampere draw with rock brittleness indexes in rock sawing process. Arch Min Sci 2011;56:777–88.
[9]     Ataei M, Mikaeil R, Hoseinie SH, Hosseini SM. Fuzzy analytical hierarchy process approach for ranking the sawability of carbonate rock. Int J Rock Mech Min Sci 2012;50:83–93. doi:10.1016/j.ijrmms.2011.12.002.
[10]    Ghaysari N, Ataei M, Sereshki F, Mikaiel R. Prediction of Performance of Diamond Wire Saw with Respect to Texture Characteristics of Rock / Prognozowanie Wydajności Pracy Strunowej Piły Diamentowej W Odniesieniu Do Charakterystyki Tekstury Skał. Arch Min Sci 2012;57. doi:10.2478/v10267-012-0058-6.
[11]    Mikaeil R, Ozcelik Y, Yousefi R, Ataei M, Mehdi Hosseini S. Ranking the sawability of ornamental stone using Fuzzy Delphi and multi-criteria decision-making techniques. Int J Rock Mech Min Sci 2013;58:118–26. doi:10.1016/j.ijrmms.2012.09.002.
[12]    Sadegheslam G, Mikaeil R, Rooki R, Ghadernejad S, Ataei M. Predicting the production rate of diamond wire saws using multiple nonlinear regression analysis. Geosystem Eng 2013;16:275–85. doi:10.1080/12269328.2013.856276.
[13]    Mikaeil R, Ataei M, Ghadernejad S, Sadegheslam G. PREDICTING THE RELATIONSHIP BETWEEN SYSTEM VIBRATION WITH ROCK BRITTLENESS INDEXES IN ROCK SAWING PROCESS. Arch Min Sci 2014;59. doi:10.2478/amsc-2014-0010.
[14]    Mikaeil R, Abdollahi Kamran M, Sadegheslam G, Ataei M. Ranking sawability of dimension stone using PROMETHEE method. J Min Environ 2015;6:263–71. doi:10.22044/jme.2015.477.
[15]    Mikaeil R, Dormishi A, Sadegheslam G, Haghshenas SS. Effect of Freezing on Strength and Durability of Dimension Stones Using Fuzzy Clustering Technique and Statistical Analysis. Anal Numer Methods Min Eng 2016.
[16]    Aryafar A, Mikaeil R. Estimation of the Ampere Consumption of Dimension Stone Sawing Machine Using of Artificial Neural Networks. Int J Min Geo-Engineering 2016;50:121–30. doi:10.22059/ijmge.2016.57861.
[17]    Mikaeil R, Haghshenas SS, Haghshenas SS, Ataei M. Performance prediction of circular saw machine using imperialist competitive algorithm and fuzzy clustering technique. Neural Comput Appl 2018;29:283–92. doi:10.1007/s00521-016-2557-4.
[18]    Mikaeil R, Ozcelik Y, Ataei M, Shaffiee Haghshenas S. Application of harmony search algorithm to evaluate performance of diamond wire saw. J Min Environ 2016. doi:10.22044/jme.2016.723.
[19]    Almasi SN, Bagherpour R, Mikaeil R, Ozcelik Y. Developing a new rock classification based on the abrasiveness, hardness, and toughness of rocks and PA for the prediction of hard dimension stone sawability in quarrying. Geosystem Eng 2017;20:295–310. doi:10.1080/12269328.2017.1278727.
[20]    Almasi SN, Bagherpour R, Mikaeil R, Ozcelik Y, Kalhori H. Predicting the Building Stone Cutting Rate Based on Rock Properties and Device Pullback Amperage in Quarries Using M5P Model Tree. Geotech Geol Eng 2017;35:1311–26. doi:10.1007/s10706-017-0177-0.
[21]    Najmedin Almasi S, Bagherpour R, Mikaeil R, Ozcelik Y. Analysis of bead wear in diamond wire sawing considering the rock properties and production rate. Bull Eng Geol Environ 2017;76:1593–607. doi:10.1007/s10064-017-1057-9.
[22]    Akhyani M, Mikaeil R, Sereshki F, Taji M. Combining fuzzy RES with GA for predicting wear performance of circular diamond saw in hard rock cutting process. J Min Environ 2017. doi:10.22044/jme.2017.5770.1388.
[23]    R M, S SH, M A, S SH. The Application of Multivariate Regression Analysis to Predict the Performance of Diamond Wire Saw. 25th Int. Min. Congr. Exhib. Turkey, 2017, p. 122–8.
[24]    Technical report of Gazik Granit Mine. n.d.
[25]    Fatemi SAA. Economical – Technical Study of Diamond cutting weir used to granite Extraction in Gazik Mine, Birjand. Iran. Min. Eng. Conf., 2003.
[26]    Hwang C-L, Yoon K. Multiple Attribute Decision Making: Methods and Applications. vol. 186. Berlin, Heidelberg: Springer Berlin Heidelberg; 1981. doi:10.1007/978-3-642-48318-9.
[27]    Yoon K. System selection by multiple attribute decision making. Ph.D. Dissertation, Kansas State University, Manhattan, Kansas, 1980.
[28]    Ataei M. Site Selection of Alomina- Cement Plantation Construction using Topsis Method. Amir Kabir J n.d.;16:84–7.
[29]    Wang T-C, Chang T-H. Application of TOPSIS in evaluating initial training aircraft under a fuzzy environment. Expert Syst Appl 2007;33:870–80. doi:10.1016/j.eswa.2006.07.003.
[30]    Cheng C-T, Zhao M-Y, Chau KW, Wu X-Y. Using genetic algorithm and TOPSIS for Xinanjiang model calibration with a single procedure. J Hydrol 2006;316:129–40. doi:10.1016/j.jhydrol.2005.04.022.
[31]    Shanian A, Savadogo O. TOPSIS multiple-criteria decision support analysis for material selection of metallic bipolar plates for polymer electrolyte fuel cell. J Power Sources 2006;159:1095–104. doi:10.1016/j.jpowsour.2005.12.092.
[32]    Wang Y-M, Elhag TMS. Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment. Expert Syst Appl 2006;31:309–19. doi:10.1016/j.eswa.2005.09.040.
[33]    Jahanshahloo GR, Lotfi FH, Izadikhah M. Extension of the TOPSIS method for decision-making problems with fuzzy data. Appl Math Comput 2006;181:1544–51. doi:10.1016/j.amc.2006.02.057.
[34]    Wang Y-J, Lee H-S. Generalizing TOPSIS for fuzzy multiple-criteria group decision-making. Comput Math with Appl 2007;53:1762–72. doi:10.1016/j.camwa.2006.08.037.
[35]    Lin M-C, Wang C-C, Chen M-S, Chang CA. Using AHP and TOPSIS approaches in customer-driven product design process. Comput Ind 2008;59:17–31. doi:10.1016/j.compind.2007.05.013.
[36]    Chen T-Y, Tsao C-Y. The interval-valued fuzzy TOPSIS method and experimental analysis. Fuzzy Sets Syst 2008;159:1410–28. doi:10.1016/j.fss.2007.11.004.
[37]    Ertuğrul İ, Karakaşoğlu N. Performance evaluation of Turkish cement firms with fuzzy analytic hierarchy process and TOPSIS methods. Expert Syst Appl 2009;36:702–15. doi:10.1016/j.eswa.2007.10.014.
[38]    Saaty TL. Decision making for leade. 2001.
[39]    Liu Y-C, Chen C-S. A new approach for application of rock mass classification on rock slope stability assessment. Eng Geol 2007;89:129–43. doi:10.1016/j.enggeo.2006.09.017.
[40]    Kabassi K, Virvou M. A technique for preference ordering for advice generation in an intelligent help system. 2004 IEEE Int. Conf. Syst. Man Cybern. (IEEE Cat. No.04CH37583), IEEE; n.d., p. 3338–42. doi:10.1109/ICSMC.2004.1400857.