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.

Mining, like other industries, has progressed through a series of industrial revolutions, transitioning from disconnected, manually operated mines to operations dominated by safe, sustainable, semi-automated, and automated operations, driven by technological advancements such as digitalisation and automation. These changes have resulted in enhanced safety measures, cost reductions, and increased efciency, while simultaneously altering the nature of mining work. This paper presents a study to assess the impacts, challenges, and opportunities of automation and digitalisation in the mining industry from an end-user’s perspective. The study is based on the overall combined results from two previous studies, one surveying the opinions of LHD operators and the other the opinions of mining production workers, extracted through two workshops. The fndings indicate digitalisation and automation are predominantly perceived positively, but there are some negative attitudes. End-users have diverse opinions about the impact of digitalisation and automation on their work and the skill sets that will be required in the future, but they agree computer skills and understanding of the mining processes will continue to be crucial competencies in the future. Another common opinion is that machine maintenance is the most challenging aspect of the work to automate. The results highlight an increased need for further education enabling workers to manage new technologies as they are implemented.

Mining is a high-risk industry, so efficiency and safety are key priorities. As mines continue to go deeper and exploit low-grade deposits, bulk mining methods, such as sublevel caving (SLC), have become increasingly important. SLC is suitable for massive steeply dipping ore bodies and is known for its high degree of mechanisation, productivity, and low operational cost. Moreover, technological developments and mechanisation have allowed these methods to be applied at greater depths. In modern mechanised mines Load haul dump (LHD) machines are central to achieving the desired productivity. Therefore, automation of LHDs and their increasing use in mines make it crucial to understand the performance of these machines in actual mining environments. The aim of this research was to understand the differences in the productivity of semiautonomous and manual LHDs and identify how external factors impact the performance of these machines in SLC operations. The research also investigated how LHD operator training could improve the loading efficiency.

Performance data for semi-autonomous and manual LHDs were collected from LKAB’s Kiirunavaara mine’s central database, GIRON. These data were used to compare cycle times and payloads of semi-autonomous and manual LHDs. The data were filtered and sorted so that only data where both machine types were operating in the same area (crosscut, ring, and ore pass) were used. To understand the impact of external factors, data on the occurrence of boulders were collected from LKAB’s Malmberget mine by recording videos of LHD buckets, while the data on operator training were obtained by performing baseline mapping and conducting a questionnaire study with the LHD operators at LKAB’s Kiirunavaara mine.

The results of the comparative analysis of manual and semi-autonomous LHDs showed the mean payload was 0.34 tonnes higher for manual LHD machines. However, the differences were not consistent across different areas of the mine. Similarly, when comparing the cycle times, in 57% of the studied area, manual LHDs had lower cycle time, while the opposite was true in the remaining 43% of the areas. Therefore, the differences in cycle time and payload due to mode of operation are not conclusive, meaning that one machine type does not completely outperform the other. This highlights the importance of understanding the external factors that cause such differences. Moreover, the findings emphasize the need to upgrade LHD operator training based on pedagogical principles and the inclusion of new technologies to enhance loading efficiency and increase overall productivity.

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.

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.