The aim of the research is to assess the applicability of robotics and automation technologies to enhance safety performance and operational efficiency in mining operations in surface, underground, and coal mining settings. A mixed-methods and systematic approach was embraced, which involved the secondary data through peer-reviewed publications, industrial reporting, and reported mining cases. The applicability of autonomous haulage systems, robotic drilling and inspection systems, UAVs, patrol robots, swarm robotics, and intelligent sensor networks was evaluated based on the main safety and efficiency indicators. A coherent analytical system was established in order to compare the correlation of accident minimization, reduction of exposure to workers, productivity improvement, and equipment functionality in various mining conditions. The findings reveal that there was a great safety enhancement, and the rates of reduction of accidents are 39.1% in surface mining, 51.4% in underground mining, and 48.0% in coal mining. In underground operations, exposure of workers to hazardous areas was reduced by up to 58.9%. There was also a significant improvement in the operational efficiency, whereby there was an increment of equipment use by 30.7%, productivity output by 31.6%, a reduction in the cycle time by 30.8%, and a decline in the unplanned downtime by 45.3%. The greatest combined benefit was seen in underground mining based on the integrated Safety -Efficiency Index (SEI = 17.6). The results prove that robotics and automation allow improving safety and efficiency simultaneously, especially in the high-risk mining areas, which facilitates the shift toward safer and more sustainable mining processes.
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