The scientific assessment of rock mass blastability performs two key roles by providing vital guidance for engineering blasting plan design and optimization, as well as creating essential standards for choosing suitable drilling equipment, explosives, and related blasting materials. A systematic evaluation approach integrating conventional Analytic Hierarchy Process(AHP) methodology with extension matter-element modeling was developed to assess rock mass blastability characteristics at the SICOMINES Copper-cobalt Mine in the Democratic Republic of the Congo with scientific rigor and practical feasibility. The study identifies four key assessment parameters for rock mass blastability classification that align with both the evaluation framework and site-specific mining conditions, including rock type(X₁), compressive strength(X₂), ore-rock density(X₃), and tensile strength(X₄). An extension of the matter element model was constructed to classify the blastability of the rock mass in the study area into 5 distinct categories, ranging from grade Ⅰ, representing extremely easy blasting conditions, to grade Ⅴ, indicating extremely difficult blasting conditions. Intermediate grades Ⅱ, Ⅲ, and Ⅳ correspond to easy, medium, and difficult blasting conditions, respectively. The correlation degree matrix analysis was performed to assess blastability characteristics of three geological layers(CMN, RAT, and RSC) in the mining area, with results indicating grade Ⅳ(difficult) for the CMN layer, grade Ⅲ(medium) for the RAT layer, and grade Ⅱ(easy) for the RSC layer, demonstrating strong alignment with observed field conditions. The findings demonstrate that this approach requires minimal training, uses sample features and straightforward calculations, and has high practical applicability, while serving as both a valuable foundation for engineering blasting design optimization and an innovative technique for assessing rock mass blastability.

In order to study the development track and hot spot changing trends of blasting technology in open-pit mining, 1116 valid journal articles were retrieved as a sample from the China National Knowledge Infrastructure(CNKI) database by selecting “open-pit mining” and “blasting” as the search criteria. According the visual analysis reports from CNKI and utilizing the visual knowledge graph tool CiteSpace, a comprehensive and in-depth study has been conducted on the state of the art, distribution characteristics, research hotspots, and cutting-edge trends in the field of open-pit mining blasting research in China. The research findings indicate that the study of open-pit mining blasting has undergone three distinct stages: the establishment and development of open-pit mining blasting theory(pre—2010), the phase of modern technology application and innovation(2010—2015), and the stage of green, intelligent, and precision development(2015—present). The disciplinary distribution primarily focuses on mining engineering and general industrial technology and equipment. The prominent journals for publication include Blasting, Engineering Blasting, and other journals in the field of mining engineering. The majority of authors and institutions are affiliated with mining-related universities, enterprises and research institutes. The research topics encompass various aspects, including the development and application of blasting design software, optimization of blasting parameters(such as blast hole pattern, powder factor and charge structure), deep-hole blasting, bench blasting, cast blasting, pre-splitting blasting, control and monitoring of blasting vibration, numerical simulation, and application of artificial intelligence algorithms, analysis of factors affecting blasting quality and evaluation of blasting effects. The future of open-pit mining blasting will continue to evolve towards automation, intelligence, precision and environmental friendliness. Through technological innovation and interdisciplinary integration, the industry aims to provide more efficient, safer and sustainable blasting solutions for the mining sector.