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One of the most hazardous fields of engineering is mining operations and accordingly, it requires extra consideration on risk evaluation. Decorative stone quarrying is one of the main branches of the mining industry in Iran. Currently, Iran, China and Italy are known as the three main producers of decorative stones in the world. Subsequently, risk assessment is one of the main steps of quarrying organization. One of the main steps of risk assessment is Risk Breakdown Structure (RBS). In order to achieve this goal, a comprehensive structure of dimensional stone quarrying is modelled in this research and divided into 17 main levels. One of the most useful procedures of risk ranking is Multi attribute decisionmaking methods which state that they have numerous affecting parameters. In the next step of this study, the main hazards of main decorative stone quarrying are assessed by implementing the 'Preference Ranking Organization Method for Enrichment Evaluation' (PROMETHEE) technique. As a final point, Economical, Management, and Schedule risks are determined as the most intimidating hazards in this field.

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Given the increasing demand for dimension stones, mining operations in quarries have always been an important branch of mining engineering. Among different techniques, diamond wire cutting is one of the most common methods of dimension stone mining. A reliable assessment and accurate prediction of diamond wire cutting performance are essential for feasibility analysis and operational planning in this area. This performance depends on factors such as physical, mechanical, and textural properties of the rock and the characteristics of cutting operations which can be evaluated by criteria such as specific energy, production rate, efficiency, and diamond bead wear rate. This study aims to develop a method for predicting the specific energy of diamond wire cutting in dimension stones based on rock properties. For this purpose, the specific energy of diamond wire cutting in 11 different igneous rock samples was measured. Given the high strength and abrasivity of igneous rocks, cutting operations in these rocks generally requires a great amount of energy. In a series of tests performed on the samples, rock properties such as uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), Young's modulus, density, textural properties, abrasivity and operating factors such as pullback amperage were measured. The measured parameters were divided into four groups of physical, mechanical, textural, and operating parameters. After determining the specific cutting energy of each sample, the relationship of the energy with each individual property was investigated. This investigation showed that density, abrasivity, and p-wave velocity respectively had the highest correlation with specific energy. Using the correlation results, four input parameters (one from each of the four considered parameter groups) were selected for inclusion in the prediction model. These parameters were density, abrasivity, wave velocity, and amperage. Multivariate linear regression was then used to analyse the effect of rock properties and operating parameters on specific energy. The developed regression model showed that once the rock properties are known, the specific energy can be predicted with an accuracy of 85.8%. The proposed model can be used to estimate the specific energy of diamond wire cutting operations in dimension stone quarries in advance, and predict the amount of energy consumption, the required energy source, and the optimal cutting machine accordingly.