iron ore crusher selection criteria work

primary crusher selection & design

The crusher capacities given by manufacturers are typically in tons of 2,000 lbs. and are based on crushing limestone weighing loose about 2,700 lbs. per yard3 and having a specific gravity of 2.6. Wet, sticky and extremely hard or tough feeds will tend to reduce crusher capacities.

Selectiingwhat size a crusher needs to be is based on factors such as the F80 size of the rocks to be crushed, the production rate, and the P80 desired product output size. Primary crushers with crush run-of-mine rock from blast product size to what can be carried by the discharge conveyor or fit/math the downstream process.A typical example of primary crushing is reducing top-size from 900 to 200 mm.

Ultimately, the mining sequence will certainly impact the primary crusher selection. Where you will mine ore and where from, is a deciding factor not so much for picking between a jaw or gyratory crusher but its mobility level.

The mom and dad of primary crushers are jaw and gyratory crushers. In open-pit mines where high tonnage is required, thegyratory crushers are typically the choice as jaw crushers will not crush over 500 TPH with great ease. There are exceptions like MPI Mineral Park in AZ where 50,000 TPD was processed via 2 early century vintage jaw crushers of a:

The rated capacity at 5 closed-side setting was 490 stph based on standard 100lbs/ft3 feed material. These crushers were fed a very fine ore over a 4 grizzly which allowed the 1000 TPH the SAG mills needed.

In under-ground crushing plants where the diameter of the mine-shaft a skip forces limits on rock size, a jaw crusher will be the machine of choice. Again, if crushing on surface, both styles of stone crushing machines should be evaluated.

application of analytical hierarchy process to selection of primary crusher - sciencedirect

Selection of crusher required a great deal of design based on the mining plan and operation input. Selection of the best primary crusher from all of available primary crushers is a Multi-Criterion Decision Making (MCDM) problem. In this paper, the Analytical Hierarchy Process (AHP) method was used to selection of the best primary crusher for Golegohar Iron Mine in Iran. For this reason, gyratory, double toggle jaw, single toggle jaw, high speed roll crusher, low speed sizer, impactor, hammer mill and feeder breaker crushers were considered as alternatives and capacity, feed size, product size, rock compressive strength, abrasion index and mobility of crusher were considered as criteria. As a result of our study, the gyratory crusher was offered as the best primary crusher for the studied mine.

fuzzy topsis method to primary crusher selection for golegohar iron mine (iran) | springerlink

Selection of the crusher required a great deal of design regarding to the mine planning. Selection of suitable primary crusher from all of available primary crushers is a multi-criterion decision making (MCDM) problem. The present work explores the use of technique for order performance by similarity to ideal solution (TOPSIS) with fuzzy set theory to select best primary crusher for Golegohar Iron Mine in Iran. Gyratory, double toggle jaw, single toggle jaw, high speed roll crusher, low speed sizer, impact crusher, hammer mill and feeder breaker crushers have been considered as alternatives. Also, the capacity, feed size, product size, rock compressive strength, abrasion index and application of primary crusher for mobile plants were considered as criteria for solution of this MCDM problem. To determine the order of the alternatives, closeness coefficient is defined by calculating the distances to the fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS). Results of our work based on fuzzy TOPSIS method show that the gyratory is the best primary crusher for the studied mine.

GLIGORIC Z, BELJIC C, SIMEUNOVIC V. Shaft location selection at deep multiple orebody deposit by using fuzzy TOPSIS method and network optimization [J]. International Journal of Expert Systems with Applications, 2010, 37(2): 14081418.

TORFI F, ZANJIRANI FARAHANI R, REZAPOUR S. Fuzzy AHP to determine the relative weights of evaluation criteria and fuzzy TOPSIS to rank the alternatives [J]. Applied Soft Computing, 2010, 10(2): 520528.

ALAVI I, ALINEJAD-ROKNY H. Comparison of fuzzy AHP and fuzzy TOPSIS methods for plant species selection (case study: Reclamation plan of Sungun Copper Mine; Iran) [J]. Australian Journal of Basic and Applied Sciences, 2011, 5(12): 11041113.

FOULADGAR M M, YAZDANI-CHAMZINI A, ZAVADSKAS E K. An integrated model for prioritizing strategies of the Iranian mining sector [J]. Technological and Economic Development of Economy, 2011, 17(3): 459483.

SAFARI M, KAKAEI R, ATAEI M, KARAMOOZIAN, M. Using fuzzy TOPSIS method for mineral processing plant site selection, Case study: Sangan Iron Ore Mine (phase 2) [J]. Arabian Journal of Geoscience, 2012, 5: 10111019.

SAGHAFIAN S, HEJAZI A R. Multi-criteria group decision making using a modified fuzzy TOPSIS procedure [C]// International Conference on Computational Intelligence for Modeling, Control and Automation and Conference Intelligent Agents, Web Technologies and Internet Commerce IEEE, Vienna, 2005: 215221.

ERTURUL , KARAKAOLU N. Fuzzy TOPSIS method for academic member selection in engineering faculty [J]. M. Iskander (ed.), Innovations in E-learning, Instruction Technology, Assessment, and Engineering Education, 2007: 151156.

ROUHANI A K, HOJAT A. Determination of groundwater and geological factors using geoelectrical methods to design a suitable drainage system in Gol-e-Gohar iron ore Mine [C]// Iran, International Mine Water Association Symposium, England, 2004: 219224.

Rahimdel, M.J., Karamoozian, M. Fuzzy TOPSIS method to primary crusher selection for Golegohar Iron Mine (Iran). J. Cent. South Univ. 21, 43524359 (2014). https://doi.org/10.1007/s11771-014-2435-0

equipment selection in mineral processing - a sensitivity analysis approach for a fuzzy multiple criteria decision making model - sciencedirect

A new sensitivity analysis approach for multi criteria decision making is proposed.The approach considers the main notions of a new hybrid decision making technique.The approach is used to analyse a crusher selection problem.The best alternative was not altered by varying the analysed parameters.The approach can provide comprehensive information on the decision making results.

Selecting the most suitable mineral processing equipment among feasible alternatives with respect to multiple conflicting criteria is considered a Multiple Criteria Decision Making (MCDM) problem. For example, a type of crusher that might allow a very high throughput is less likely to be used in a mobile plant, so trade-offs between these type of criteria need to be clearly defined in the decision making process. One of the most frequently used MCDM methods is the Analytical Hierarchy Process (AHP) method, which relies on judgements from decision makers that allow for comparisons to be made between alternatives (e.g. the type of equipment) or criteria (e.g. the characteristics of the equipment that are of interest). However, AHP is not able to capture the uncertainty associated with the various decision makers judgements and the lack of precise information. An integrated constrained fuzzy stochastic analytic hierarchy process (IC-FSAHP) is a new hybrid MCDM method that can be used to overcome the aforementioned limitations of AHP. In order to understand the robustness of AHP based methods, a sensitivity analysis of the decision making results is required. However, sensitivity analyses are not often carried out for fuzzy AHP methods, arguably because of the complexity of some of the procedures involved, the computation time required and the limited resources available to do so. The main objective of this paper is therefore to propose a new sensitivity analysis approach by applying an additional fuzzification factor and disagreement level of decision makers in order to model uncertainty. For this purpose, a case study for the selection of primary crushers was considered. Five types of primary crushers were evaluated with respect to six criteria to showcase the applicability of the proposed approach to assess IC-FSAHP. The results obtained showcase that the proposed sensitivity analysis approach is capable of providing extensive and useful what-if information on the decision making results.