Drilling and blasting remain the preferred technique used for rock mass breaking in mining and construction projects compared to other methods from an economic and productivity point of view. However, rock mass breaking utilizes only a maximum of 30% of the blast explosive energy, and around 70% is lost as waste, thus creating negative impacts on the safety and surrounding environment. Blast-induced impact prediction has become very demonstrated in recent research as a recommended solution to optimize blasting operation, increase efficiency, and mitigate safety and environmental concerns. Artificial neural networks (ANN) were recently introduced as a computing approach to design the computational model of blast-induced fragmentation and other impacts with proven superior capability. This paper highlights and discusses the research articles conducted and published in this field among the literature. The prediction models of rock fragmentation and some blast-induced effects, including flyrock, ground vibration, and back-break, were detailed investigated in this review. The literature showed that applying the artificial neural network for blast events prediction is a practical way to achieve optimized blasting operation with reduced undesirable effects. At the same time, the examined papers indicate a lack of articles focused on blast-induced fragmentation prediction using the ANN technique despite its significant importance in the overall economy of whole mining operations. As well, the investigation revealed some lack of research that predicted more than one blast-induced impact.

The conventional blasting rock excavation method is the main means of rock breakage because of its high productivity, and it is relatively inexpensive compared to other methods. However, it raises safety concerns and can negatively impact the environment. The major disturbances that may be induced by this method include flyrock, gas emissions, and vibrations. This review discusses some nonexplosive rock breakage methods, particularly the hydraulic splitter and expansive chemical agents, that can be employed instead of the conventional blasting method and analyzes their potential effectiveness in rock breakage. Hydraulic splitting machines and expansive chemical agents were studied in the context of the literature. This review showed that hard rock breaking can be executed effectively and safely using alternative methods, which have a wide range of advantages, including safe operation, ease of use, and environmental friendliness, over conventional explosive methods. Moreover, as modern nonexplosive methods, hydraulic splitting machines and expansive chemical agents can generate pressure of up to 43 and 30–44 MPa to induce stresses in rocks, respectively. Owing to safety and environmental restrictions on conventional blasting, the application scope of the modern methods can be increased in the future.

Over many decades, cement has been the primary component in construction projects and is considered one of the essential industries worldwide. At the same time, it overconsumes natural resources and can negatively impact the environment through a few byproducts, such as carbon dioxide (CO2) and cement kiln dust (CKD). The generated quantity of CKD is estimated to be 15–20% of the produced cement, which means CKD can be induced in hundreds of millions of metric tons synchronously with annual global cement production. Unfortunately, not all materials of CKD are suitable for recycling in cement manufacturing since it contains high levels of alkalis, sulfate, and chloride, leading to excessive concentrations in the final product. Therefore, CKD industrial utilization has become highly recommended in recent research as a potential beneficial application from economic, environmental, and sustainability perspectives. This review paper highlights and discusses the recently conducted research articles that investigate the industrial applications of CKD. The obtained outcomes showed that CKD has physical and chemical properties that make it practical in many fields, such as soil stabilization, concrete mix, chemical treatment, ceramic and brick manufacturing, and mine backfill. They also indicate a lack of studies investigating CKD in mine backfill applications as a partial replacement material for cement due to the high cost of binders, optimization, and sustainability purposes.

Cement global demand shows continued growth and a significant increase in the production volume, which may negatively impact the non-renewable natural resources and the environment, which is incompatible with sustainability goals. Cement kiln dust (CKD) is a primary concern associated with clinker manufacturing as a waste byproduct. Similarly, the mining industry produces copper tailing as unwanted material while beneficiating the ore, creating environmental problems due to difficulty in managing worldwide generated quantities that reach billions of metric tons. This study investigated the beneficial utilization of cement kiln dust and copper tailing as undesirable wastes in industrial applications through underground mines’ cemented paste backfill (CPB). Sixty different mixtures were prepared with three types of CKD collected from various cement manufacturers and were accordingly used with a proportion of 5, 10, and 15% to partially replace ordinary Portland cement (OPC) and pozzolan Portland cement (PPC) binders, represented in hundreds of CPB samples. The hardened specimens were subjected to density, uniaxial compressive strength (UCS), and axial deformation measurements to evaluate the physical and mechanical properties at curing up to 90 days. Meanwhile, X-ray powder diffraction (XRD) was extensively applied to chemically investigate the hydration products of CPB-hardened mixtures. Moreover, we developed a UCS predictive model applying two techniques: multiple variables regression analysis and artificial neural network (ANN). The results showed that the tricalcium silicate (Alite) and dicalcium silicate (Belite) phases form C-S-H upon hydrations and provide high strength in the binary mixtures. Meanwhile, the CKD’s lime saturation factor (LSF) governed the strength value in the ternary mixtures that utilized copper tailings. That makes CKD practical in the CPB mixture when partially replacing the OPC and PPC binders, with a proportion of up to 15%. In addition, the ANN technique’s predictive model exhibited a significant positive correlation with excellent statistical parameters that achieved 0.995, 0.065, and 0.911 for R2, RMSE, and MAE, respectively.

Mining still plays a vital role in providing various sectors with essential materials since many industries depend heavily on mined minerals. Moreover, the mining industry is the primary driver for many economies worldwide. On the other hand, new mining projects face many challenges, the most important of which are risks related to the economic aspects, e.g., the significant uncertainty about mineral resources compared to other engineering projects. Therefore, many jurisdictions worldwide depend on detailed engineering studies conducted according to internationally recognized standards to assess the new mining projects from an economic and technical perspective. In the same context and due to the significant lack of published research in this field, as the literature review revealed, this article reviewed and discussed the different main stages of engineering studies to evaluate new potential mining projects, including scoping, pre-feasibility, and feasibility studies, to ensure that the engineering study report complies with all the recognized main requirements. Results indicated the necessity of adhering to the needs of the engineering tasks while preparing reports of evaluation studies for new mining projects to reduce potential uncertainty risks and thus raise the level of confidence in these types of projects. Furthermore, they showed direct progress between the investigation details conducted in the evaluation studies and the value of the new mining project.