Decision-making is very important in many fields, such as mining engineering. In addition, there has been a growth of computer applications in all fields, especially mining operations. One of these application fields is mine design and the selection of suitable mining methods, and computer applications can help mine engineers to decide upon and choose more satisfactory methods. The selection of mining methods depends on the rock-layer specification. All rock characteristics should be classified in terms of technical and economic concerns related to mining rock specifications, such as mechanical and physical properties, and evaluated according to their weights and ratings. Methodologically, in this study, the criteria considered in the University of British Columbia (UBC) method were used as references to establish general criteria. These criteria consist of general shape, ore thickness, ore plunge, and grade distribution, in addition to the rock quality designation (ore zone, hanging wall, and foot wall) and rock substance strength (ore zone, hanging wall, and foot wall). The technique for order of preference by similarity to ideal solution (TOPSIS) was adopted, and an improved TOPSIS method was developed based on experimental testing and checked by means of the application of cascade forward backpropagation neural networks in mining method selection. The results provide indicators that decision makers can use to choose between different mining methods based on the total points given to all ore properties. The best mining method is cut and fill stopping, with a rank of 0.70, and the second is top slicing, with a rank of 0.67.

A new non-dispersive, anti-washout grout consisting of ordinary Portland cement, slag, superplasticizer, and methylbenzyl cellulose is proposed herein for the treatment of open karst, jointed and fractured rock, open-work gravel, and permeable sediments. A series of laboratory experiments were performed to design an anti-wash out grout suitable for grout injection of coarse aggregates depicting partially and open-jointed saturated rock mass and grouting concrete aggregates for underwater construction. The Taguchi orthogonal array was used to obtain nine different grout mix ratios. A total of four variables were considered, each with three different levels of the water–cement ratio, slag, and dosage of additives such as the superplasticizer and methyl benzyl cellulose. The laboratory determination of grout characteristics recording of mini slump, temperature, pH, visual assessment of grout dispersion, bleeding, and initial setting time and as well as uniaxial compressive strengths and permeabilities of the hardened grout samples were tested. To evaluate the suitability of the grout mixes, an analysis of variance was used for factor analysis and Grey relational analysis (GRA) was used to determine the optimal grout mix design. Based on the GRA, the following levels of the factors afforded the best results: water level 1 (0.3%), SP level 3 (0.01%), methylbenzyl cellulose level 2 (0.002%), and slag level 3 (0.1%). This paper describes the research methodology, detailed research observations, and analyses involved in designing the appropriate concrete mix. Based on the conclusions, relevant commendations regarding the suitability of grout testing equipment and grout mix designs are presented.

The ornamental stones industry has grown progressively in Egypt as the demand has increased for Egyptian decorative stones in indoor and outdoor building spaces. Choosing the most suitable ornamental stone for each purpose and taking the right decisions related to aesthetic and practical performance can be a challenge causing a lot of confusion for homeowners and contractors. Thus, there is a need to define what decorative style you are trying to achieve in order to properly choose the most suitable decorative stone. In this research, some Egyptian ornamental stones were evaluated by combining the analytic hierarchy process (AHP) and the technique for order preference by similarity to ideal solution (TOPSIS). The optimized AHP–TOPSIS comprehensive decision model was implemented on natural materials relevant to ornaments and the finishing purposes of indoor and outdoor buildings. Ten rock types from four Egyptian sites were studied, examined, and analyzed. According to the quality index scheme, grey granite is an ideal ornamental stone that meets indoor and outdoor purposes. Grey granite and black marble have a performance score (Pi) of 0.78 and 0.71, respectively. Serpentine and pink granite were ranked third with a Pi = 0.68. These results provide stakeholders with strategic indicators to select different natural ornamental stones based on the total points assigned to all rock specifications and costs.

Digital transformation (DT) is defined as a strategy for boosting mining assets by attempting significant changes to of own properties through the integration of communication, data computing, and property technologies. Making large-scale changes will be difficult with digital technology, especially if the business is not well-positioned to do so. Increasing cybersecurity protection levels is the most effective way to ensure the success of the transformation. When making significant changes, a clear digital vision should be outlined and implemented with strong leadership. However, the majority of digital transformation initiatives fail before they are completed. The problem does not just affect the mining industry. The purpose of this paper is to investigate the major challenges encountered in digital transformation projects and to propose a strategic solution for implementing and scaling digital initiatives.

At great depths, tunnel openings experience a tectonic stress field rather than overburden stress. This paper aims to examine the impact of different in situ stress ratios and multiple tunnel depths below the surface on the excavation induced-stresses and displacements around tunnel openings. Thus, a series of models has been built, using a two-dimensional elasto-plastic finite-elements code, RS2D, to conduct parametric stability analysis. The performance of tunnel opening is examined by evaluating the induced stress-deformation around the opening. The results indicate that ratio of wall convergence, roof sag and floor heave increase as in situ stress ratio and tunnel depth below surface increase. Additionally, the induced-stresses increase as depth and state of in situ stress increase. In addition, the extent of yielding zones into rock mass around tunnel roof and floor deteriorates as tunnel depth and in situ stress ratio increase. Moreover, the normal stress along rock joints is sharply dropped when joints pass in the vicinity of tunnel opening (e.g., centre of opening). As well, the direction of shear stress along joints is reversed. Consequently, inward shear displacement of rock, on the underside of the weakness plane, is produced as a result of slip occurrence.

The most crucial event in a mining project is the selection of an appropriate mining method (MMS). Consequently, determining the optimal choice is critical because it impacts most of the other key decisions. This study provides a concise overview of the development of multiple selection methods using a cascade‐forward backpropagation neural network (CFBPNN). Numerous methods of multicriteria decision‐making (MCDM) are discussed and compared herein. The comparison includes several factors, such as applicability, subjectivity, qualitative and quantitative data, sensitivity, and validity. The application of artificial intelligence is presented and discussed using CFBPNN. The Chengchao iron mine was selected for this investigation to pick the optimum mining method. The results revealed that cut and fill stoping is the most appropriate mining method, followed by sublevel and shrinkage stoping methods. The least appropriate method is open‐pit mining, followed by room and pillar and longwall mining methods.