Abstract
Surface mining operations are often measured by volumetric movement. The ability of operations to meet volume targets depends on several factors, foremost of which are productivity and efficiency of equipment. Achieving target volumes is important for the economic and social well-being of mining regions and nations because mines are required to yield a return on investment for shareholders. Efficient operations can halve capital payback periods on equipment through higher productivities which have a revenue value. This emphasises the importance of productivity as a key performance measure.
Mining, though operationally complex, can be viewed as a socio-technical system which integrates both technological and social subsystems. The mining cycle, which involves activities such as drilling, blasting, loading and hauling, has both social and technical components primarily in the form of equipment and their respective operators. This study shows that operator variability can account for up to 16% in mining shovel productivity which has an impact on the mining cycle. This cycle is a key driver of operational revenue, where effective management of the cycle, through optimisation of productivity in both machinery and labour, is critical in efficient resource extraction.
Research has focused on automation of mining equipment in different studies, exploring how this can improve productivity. Machines are automated to mimic best-in-class operator practices. It is a particularly complex endeavour that is constrained by the ability to keep equipment running reliably. Meanwhile, less attention has been given to understanding the influence of labour resources on productivity in mining operations more exclusively. Through the principles of socio-technical systems, productivity optimisation strategies should target the whole system and not just subsystems. Maximising human-machine cooperation in the socio-technical system is key to generating the greatest benefit for stakeholders. It is apparent from the mining technology literature that the focus has been on the technical subsystem rather than the social subsystem.
This research critically investigates the optimisation of mining productivity from a socio-technical perspective with the focus on equipment operators. It highlights the need to understand the factors that drive differences in characteristic operating styles from the perspective of the mining shovel operator. It proposes human factors approach to improving productivity in open-pit mining operations, which is important given that few autonomous mines are operational. Where autonomous technologies have received varied social support and differ in maturity, the optimisation of mining equipment operators as the social subsystem is greatly encouraged.