Ground vibrations from blasting are one of the main challenges faced by mines located near populated areas. To confront this challenge, Luossavaara-Kiirunavaara Aktiebolag’s Malmberget underground iron ore mine in Sweden tested a change in blast design. Specifically, it tested production holes with smaller diameter to decrease the explosive detonated per delay and thereby lower the ground vibrations. However, smaller holes normally increase hole deviation and may also influence the chargeability of the holes, both of which have a negative effect on fragmentation. Therefore, a detailed evaluation was required before a final decision could be made. To evaluate the fragmentation, field tests were carried out in two drifts of an ore body in the mine. Cameras were mounted in both drifts to record the fragmentation in every loaded bucket. The recording was configured to start by a motion detection parameter; consequently, every movement underneath the cameras was captured. The recording process continued for over a year and resulted in more than 15,000 videos. To analyse such an enormous data for fragmentation, an internally developed quick rating system (QRS) was used to evaluate a total of 7,258 loaded buckets. Blasted rock in the load–haul–dump buckets was classified as fine, medium, coarse, or oversize based on the median fragment size (X50). This paper explains the experimental setup of the test and the analysis procedures. The test results showed that smaller diameter boreholes tend to reduce the median fragment size slightly, and therefore favour the reduction of borehole diameter to deal with the ground vibration problem. The influence of borehole deviation and chargeability was not specifically investigated in this test and need further research to better understand subsequent fragmentation variations.

Mining is a high-risk industry, so efficiency and safety are key priorities. Technological advancements, such as digitisation, digitalisation, and automation have made mines safer. These developments have also highlighted the need for operators with updated skills and improved education programs. This study analysed the training of semi-autonomous and manual Load Haul Dump (LHD) operators’ at LKAB’s Kiirunavaara mine, focusing on operators’ training, perspective and integration of more recent tool such as simulator training. The survey questionnaire was sent to all 120 LHD operators. 86 answers were received, giving response rate of 70%. Results showed that operators generally were satisfied with how the training was structured, organised, and delivered. However, they wanted to add more topics, including practical loading, spending time with departments of other sub-processes, etc. In addition, 36% of the operators, including 20% of those operating semi-autonomous LHDs, and 80% of those operating manual LHDs, found simulator training difficult.

Automation of LHDs and their increasing use in mines make it critical to understand their performance in actual mining environments. Cycle times of semi-autonomous and manual LHDs were compared to determine their productivity differences. Manual LHDs had shorter cycle times in 57% of the areas, while the semi-autonomous were faster in 43% of the areas. Cycle time distributions were evaluated, and a log-logistic distribution was proposed to simulate the total cycle time, a lognormal distribution to simulate the loading duration, a logistic distribution to simulate the dumping duration, and a small extreme-value distribution to simulate the speed of semi-autonomous LHDs.