Artificial Intelligence-Based Optimizing Blasting Practices in Mining

The advancement of artificial intelligence (AI) has transformed almost all sectors. It has been used to optimize operations for cost reduction, time management, and anomaly detection to reduce operational risk. Despite the emergence of hybrid AI models, the mining industry has not given significant attention. In mining, blasting is frequently used both on the surface and underground. It is considered to be the most cost-effective method. Although the efficiency of mine blasting has improved significantly over the last few decades, blasting still has some inevitable limitations. Blasting risks such as blast-induced ground vibration, flying rock, overbreak, and backbreak caused by blasting should be considered prior to the blasting design stage. Therefore, this study aims to assess the limitations and strengths of each existing AI model and to address the potential development of AI approaches in the mining industry.