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Nowadays, one of the most significant problems in mining activities is the significance of analyzing environmental issues along with mining, concentration, and mineral processing operations to achieve the goals of sustainable development. Nevertheless, mine owners refuse to include environmental costs (EC) and consider them unprofitable. Due to the ever-increasing importance of environmental and social topics in recent years, there is a vital need for assessing the EC and its impact on total mining costs and implementing green strategies by the mining managers and engineers. The current study tries to model the mining cost structure by considering the causal relationships between different factors affecting open-pit mining costs to highlight the EC’s role. Furthermore, this research evaluates the effectiveness of implementing each possible mining green strategy in a large-scale copper mine using the System Dynamics (SD) approach. In this regard, seven scenarios and a combination of different environmental strategies, including mine reclamation, an environmental strategy for a condensation and processing plant, and environmental mining operations, have been considered for the SD-based economic analysis. The simultaneous use of the green mining strategies for the concentration and processing plant (Scenario 4) shows a high impact on cost reduction in the mining operation.

The determination of the location of production and ventilation shafts is one of the most important issues in underground mines from both a technical and an economic viewpoint. This study introduces an integrated approach using fuzzy cognitive map (FCM) and fuzzy multi-objective optimization by ratio analysis (FMOORA) to evaluate several candidate shaft locations and consequently increase ore production from underground mines. The FCM based on a hybrid learning algorithm was applied to analyse interactions and internal relationships between criteria and to find complex causal relationships between different factors. After importing the weights resulting from the FCM into the FMOORA, shaft alternatives were evaluated and prioritized. An iron ore case example was evaluated by the integrated approach. Results of the integrated approach were validated by the results obtained from fuzzy-TOPSIS and on-site evaluations by mining experts.

One of the most significant factors in the estimation of dimension stone quarry cost is the production rate of rock cutting machines. Evaluating the production rate of chain-saw machines is a very significant and practical issue. In this research, it has been attempted to evaluate and select the suitable working-face for a quarry by examining the maximum production rate in the Dehbid and Shayan marble quarries. For this purpose, fi eld studies were carried out which included measuring operational characteristics of the chain-saw cutting machine, the production rate and sampling for laboratory tests from seven active case studies. Subsequently, the physical and mechanical properties of rocks including: Uniaxial Compressive Strength (UCS), Brazilian Tensile Strength (BTS), Los Angeles abrasion, quartz content, water absorption percentage, porosity, Schmidt hardness and grain size for all sample measurements were studied after transferring the samples to a rock-mechanics laboratory. Finally, the sawability of the quarried working-faces was evaluated using the PROMETHEE multi-criteria decision-making (MCDM) model according to the physical and mechanical properties. The results of the study indicated that the number 1 and 5 working-faces from the Dehbid and Shayan quarries are the most suitable working-faces in terms of production rate with the maximum recorded production values (4.95 and 3.1 m2 /h), and with net fl ow rates (2.67 and -0.36) respectively.