اخبار و اعلانات
آمار
| تعداد نشریات | 38 |
| تعداد شمارهها | 1,408 |
| تعداد مقالات | 10,088 |
| تعداد مشاهده مقاله | 11,909,048 |
| تعداد دریافت فایل اصل مقاله | 6,961,205 |
انتخاب بهینهترین مکان و سیستم ترابری مناسب در معادن روباز با استفاده از مدل فازی تاپسیس و برنامهریزی عدد صحیح (مطالعه موردی: معدن مس زاغدره) | ||
| علوم و فنون سازندگی | ||
| دوره 6، شماره 2 - شماره پیاپی 19، آبان 1404، صفحه 25-38 اصل مقاله (1.27 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| نویسندگان | ||
| علی بامری* 1؛ جواد ضیائی2 | ||
| 1دانشجوی دکتری، دانشکده مهندسی معدن، دانشگاه صنعتی اصفهان، اصفهان، ایران | ||
| 2دکتری، دانشکده مهندسی معدن، دانشگاه صنعتی شاهرود ، شاهرود ، ایران | ||
| تاریخ دریافت: 13 بهمن 1403، تاریخ بازنگری: 05 شهریور 1404، تاریخ پذیرش: 12 آبان 1404 | ||
| چکیده | ||
| پژوهش حاضر با هدف انتخاب بهینه ترین مکان و سیستم حملونقل در معدن مس زاغدره انجام شدهاست. برای این منظور، ترکیبی از مدل فازی تاپسیس و برنامهریزی ریاضی بهکار گرفته میشود. مدل فازی تاپسیس بهعنوان ابزاری قدرتمند برای تحلیل و اولویتبندی گزینهها در شرایط عدم قطعیت، بهمنظور ارزیابی سه گزینه اصلی سیستم حملونقل، شامل سنگشکن متحرک و نوار نقاله، کامیون-نوار نقاله و نوار نقاله کامل، استفاده میشود. نتایج نشان میدهد که سیستم سنگشکن متحرک و نوار نقاله، با توجه به معیارهایی مانند بهرهوری، هزینه و کارایی، بهعنوان بهترین گزینه معرفی میشود. در بخش دوم پژوهش، برای مکانیابی مناسب سنگشکن داخل پیت (IPCC)، از مدل برنامهریزی عدد صحیح استفاده میشود. این مدل قادر است با در نظر گرفتن محدودیتها و هزینههای عملیاتی و سرمایهای، بهترین نقاط برای نصب و جابجایی سنگشکن و نوار نقاله را در طول عمر پروژه تعیین کند. نتایج نشان میدهد که در سالهای اول تا سوم، نصب سنگشکن در نقطه شماره 1 (ابتدای پیت معدن) کمترین هزینه را بهدنبال دارد و زمان انتقال مواد را کاهش میدهد. در سالهای سوم تا هفتم، جابجایی سنگشکن به نقطه شماره 2 (ابتدای پیت در سال 7) پیشنهاد میشود که مسافت حمل مواد را کوتاهتر کرده و دسترسی به منابع جدید را بهبود میبخشد. در سالهای هفتم تا سیزدهم، نقطه شماره 2 بهعنوان مکان مناسب باقی میماند و هزینههای جابجاییهای مکرر کاهش مییابد. | ||
| کلیدواژهها | ||
| فازی تاپسیس؛ برنامهریزی عدد صحیح؛ سیستم سنگشکن و نوار نقاله؛ سیستمهای ترابری معدنی | ||
| عنوان مقاله [English] | ||
| Optimization of Conveyor and Crusher System for Open-Pit Mining Using Fuzzy TOPSIS and Integer Programming | ||
| نویسندگان [English] | ||
| Ali Bameri1؛ Javad Ziaie2 | ||
| 1PhD candidate in Mining Engineering, Isfahan University of Technology, Isfahan,Iran | ||
| 2PhD in Mining Engineering, Shahrood University of Technology, Shahrood,Iran | ||
| چکیده [English] | ||
| The present study aims to select the optimal location and transport system in the Zaghder Copper Mine. To achieve this, a combination of the Fuzzy TOPSIS model and mathematical programming is utilized. The Fuzzy TOPSIS model, as a powerful tool for analyzing and prioritizing alternatives under uncertainty, is used to evaluate three main transport system options: mobile crusher and conveyor, truck-conveyor, and full conveyor system. The results indicate that the mobile crusher and conveyor system, based on criteria such as productivity, cost, and efficiency, is identified as the best option. In the second part of the study, integer programming is applied for the optimal location of IPCC. This model can determine the best locations for installing and relocating the crusher and conveyor throughout the project’s lifespan, taking into account operational and capital costs and constraints. The results show that in the first to third years, installing the crusher at location 1 (the beginning of the pit) incurs the lowest cost and reduces material transportation time. From years three to seven, relocating the crusher to location 2 (pit number 7) is suggested, which shortens the transportation distance and improves access to new resources. In years seven to thirteen, location 2 remains the optimal choice, reducing the costs of frequent relocations. | ||
| کلیدواژهها [English] | ||
| Fuzzy TOPSIS, Integer Programming, Crusher and Conveyor System, Mining Transportation Systems | ||
| مراجع | ||
|
[1] H. Taherkhani and R. Doostmohammadi, “Transportation costs: A tool for evaluating the effect of rock mass mechanical parameters on blasting results in open pit mining,” J. Min. Sci., vol. 51, pp. 730–742, 2015. [2] L. Zhang and X. Xia, “An integer programming approach for truck-shovel dispatching problem in open-pit mines,” Energy Procedia, vol. 75, pp. 1779–1784, 2015. [3] M. Javanshirgiv and M. Safari, “The selection of an underground mining method using the fuzzy topsis method: A case study in the Kamar Mahdi II fluorine mine,” Min. Sci., vol. 24, 2017. [4] F. Sitorus, J. J. Cilliers, and P. R. Brito-Parada, “Multi-criteria decision making for the choice problem in mining and mineral processing: Applications and trends,” Expert Syst. Appl., vol. 121, pp. 393–417, 2019. [5] F. S. Namin, A. Ghadi, and F. Saki, “A literature review of Multi Criteria Decision-Making (MCDM) towards mining method selection (MMS),” Resour. policy, vol. 77, p. 102676, 2022. [6] S. Mijalkovski, O. F. Efe, Z. Despodov, D. Mirakovski, and D. Mijalkovska, “Underground mining method selection with the application of TOPSIS method,” Geosci. Eng. J., vol. 68, no. 2, pp. 125–133, 2022. [7] M. Yavuz, “Application of the TOPSIS method to solve some decision-making problems in mining operations,” J. Undergr. Resour., vol. 2, pp. 21–34, 2012. [8] O. Rivera Letelier, D. Espinoza, M. Goycoolea, E. Moreno, and G. Muñoz, “Production scheduling for strategic open pit mine planning: a mixed-integer programming approach,” Oper. Res., vol. 68, no. 5, pp. 1425–1444, 2020. [9] H. Eivazy and H. Askari-Nasab, “A mixed integer linear programming model for short-term open pit mine production scheduling,” Min. Technol., vol. 121, no. 2, pp. 97–108, 2012. [10] M. Monjezi, H. Dehghani, T. N. Singh, A. R. Sayadi, and A. Gholinejad, “Application of TOPSIS method for selecting the most appropriate blast design,” Arab. J. Geosci., vol. 5, no. 1, p. 95, 2012. [11] M. J. Rahimdel and M. Karamoozian, “Fuzzy TOPSIS method to primary crusher selection for Golegohar Iron Mine (Iran),” J. Cent. South Univ., vol. 21, pp. 4352–4359, 2014. [12] M. J. Rahimdel and R. Bagherpour, “Haulage system selection for open pit mines using fuzzy MCDM and the view on energy saving,” Neural Comput. Appl., vol. 29, pp. 187–199, 2018. [13] R. Kopa, A. S. Muji, and D. Ahmad, “Selection of Most Proper Blasting using TOPSIS Method in PT Pamapersada Nusantara Jobsite TOPB,” in Journal of Physics: Conference Series, IOP Publishing, 2019, p. 12026. [14] S. Mijalkovski, D. Peltechki, K. Zeqiri, J. Kortnik, and D. Mirakovski, “Risk assessment at workplace in underground lead and zinc mine with application of fuzzy TOPSIS method,” J. Inst. Electron. Comput., vol. 2, no. 1, pp. 121–141, 2020. [15] M. A. M. Ali and J.-G. Kim, “Selection mining methods via multiple criteria decision analysis using TOPSIS and modification of the UBC method,” J. Sustain. Min., vol. 20, no. 2, pp. 49–55, 2021. [16] G. Zhang, Y. Xue, C. Bai, M. Su, K. Zhang, and Y. Tao, “Risk assessment of floor water inrush in coal mines based on MFIM-TOPSIS variable weight model,” J. Cent. South Univ., vol. 28, no. 8, pp. 2360–2374, 2021. [17] S. Li et al., “Mining method optimization of difficult-to-mine complicated orebody using Pythagorean fuzzy sets and TOPSIS method,” Sustainability, vol. 15, no. 4, p. 3692, 2023. [18] I. Nikolić, A. Stojanović, and M. Mitrović, “A NOVEL HYBRID DECISION-MAKING MODEL: FUZZY AHP-TOPSIS APPROACH FOR PRIORITISING COPPER SMELTING PROCESSES,” Mater. Technol., vol. 58, no. 2, pp. 147–157, 2024. [19] S. Sherin and S. Raza, “Risk Analysis and Prioritization with AHP and Fuzzy TOPSIS Techniques in Surface Mines of Pakistan,” J. Min. Environ., vol. 15, no. 2, pp. 463–479, 2024. [20] L. Yin et al., “Evaluation of green mine construction level in Tibet based on entropy method and TOPSIS,” Resour. Policy, vol. 88, p. 104491, 2024. [21] M. Mohammadi, S. Hashemi, and F. Moosakazemi, “Review of in-pit crushing and conveying (IPCC) system and its case study in Copper Industry,” in World Copper Conference, 2011. [22] A. Kamrani, Y. Pourrahimian, and H. Askari-Nasab, “In-Pit Crushing and Conveying Systems in Long-term Open Pit Mine Planning–Literature,” Min. Optim. Lab., vol. 1, no. 780, p. 21, 2022. [23] D. Turnbull and A. Cooper, “In-pit crushing and conveying (IPCC)-a tried and tested alternative to trucks: Part 1,” AusIMM Bull., no. 5, pp. 60–64, 2010. [24] J. A. Dos Santos, “Theory and design of Sandwich Belt High Angle Conveyors according to the Expanded Conveyor Technology,” Bulk Solids Handl., vol. 20, no. 1, pp. 27–38, 2000. [25] J. Erodenberg, S. R. Winzer, and D. J. Nordin, “Direct dumping mining systems–Application and economics,” Int. J. Surf. Mining, Reclam. Environ., vol. 2, no. 4, pp. 193–208, 1988. [26] A. D. MacPhail and D. M. Richards, “In-pit crushing and conveying at Highland Valley Copper,” in International Journal of Rock Mechanics and Mining Sciences and Geomechanics Abstracts, 1995, p. 121A. [27] G. Konak Onur, AH & Karakus, D, “Selection of the optimum in-pit crusher location for an aggregate producer,” J. South. African Inst. Min. Metall., vol. 107, no. 3, pp. 161–166, 2007. [28] K. Boyd and R. W. Utley, “In-pit crushing design and layout consideration,” Miner. Process. plant Des. Pract. Control. Publ. by SME, vol. 1, 2002. [29] Y. Changzhi, “In-pit crushing and conveying system in Dexin pit copper haulage optimization for ore transport,” in Fifth Large Open Pit Mining Conference, 2003, pp. 49–53. [30] T. Atchison and D. Morrison, “In-pit crushing and conveying bench operations,” in Proceedings of the tenth Iron Ore Conference, 2011, pp. 123–131. [31] R. Dimitrakopoulos and S. Ramazan, “Stochastic integer programming for optimising long term production schedules of open pit mines: methods, application and value of stochastic solutions,” Min. Technol., vol. 117, no. 4, pp. 155–160, 2008. [32] J. L. E. Topal, “Strategies to assist in obtaining an optimal solution for an underground mine planning problem using Mixed Integer Programming,” Int. J. Min. Miner. Eng., vol. 3, no. 2, pp. 152–172, 2011. [33] J. Ziyayi . and L Mineri “Simulation based on multi-criteria decision making for the transportation fleet selection problem, case study of Zaghadara copper mine,” Construction Science and Technology , vol. 1, no. 4, pp. 77–89, 2021, [Online]. Available: https://stc.ihu.ac.ir/article_206064.html [34] S. Nădăban, S. Dzitac, and I. Dzitac, “Fuzzy TOPSIS: a general view,” Procedia Comput. Sci., vol. 91, pp. 823–831, 2016. [35] H. Abbaspour and C. Drebenstedt, “IPCC systems as a bulk material handling method in mines: a review regarding the technical, economic, environmental, safety and social factors,” in Proceedings of the 8th International Symposium of Young Researchers Transport Problems, 2019, pp. 785–796. [36] D. Tutton and W. Streck, “The application of mobile in-pit crushing and conveying in large, hard rock open pit mines,” in Mining Magazine Congress, Canada, 2009. [37] M. Dean, P. Knights, M. S. Kizil, and M. Nehring, “Selection and planning of fully mobile in-pit crusher and conveyor systems for deep open pit metalliferous applications,” in AusIMM 2015 3rd International Future Mining Conference, Sydney, NSW, Australia, 2015, pp. 4–6. [38] M. Osanloo and M. Paricheh, “In-pit crushing and conveying technology in open-pit mining operations: a literature review and research agenda,” Int. J. Mining, Reclam. Environ., vol. 34, no. 6, pp. 430–457, 2020. | ||
|
آمار تعداد مشاهده مقاله: 220 تعداد دریافت فایل اصل مقاله: 126 |
||