The global mining industry experiences a relatively high rate of accidents, injuries and deaths. A large number of these incidents involve interactions between people and mining equipment. This thesis describes the application of human factors methods to different parts of the design lifecycle of mobile mining equipment with the aim of encouraging more widespread adoption of these techniques. Three research studies are presented here.
In the first study (Chapter 2), injury narrative data obtained from surface coal mines in Australia were examined for human factors design issues. The injury narratives were coded using a constant comparative method that allowed categories and codes to be identified. A number of issues emerged, including the location of the person on the equipment (eg access ways) and the tasks being performed (such as maintenance). Multivariable analysis in a visual diagram allowed greater and potentially more usable information to emerge. Three specific use cases showed the benefits of greater targeting for future investigation in different areas of the mining industry. Analysis of this type should be standard in incident analysis and the methods of recording incidents should be broadened to encourage richer narrative information to be collected to allow additional trends to emerge.
The second study (Chapter 3) documented the analysis of in-depth interviews using the Critical Decision Method (CDM) with mining equipment operators who had been involved in incidents. The research found that the CDM interview method was able to identify many issues not contained within the original incident reports. The insights provided through the use of CDM could also help target redesign interventions at mine site, especially linked to mobile equipment redesign. Useful insights were frequently obtained from drawing the incident on a whiteboard. The data from each of the CDM interviews were then placed on the decision ladder. The results revealed that operators were very frequently ‘shortcutting’ a full decision making process. indicating that design solutions which address the immediate environment of the operator could prove more effective than interventions like knowledge-based retraining. However, in a practical sense, the combining of CDM outputs with the decision ladder did not offer substantially greater design solutions than may have been gained through other approaches.
Chapter 4 examined an in-cab proximity detection system installed at an underground gold mine. The goal of the system was to make drivers of haul trucks more aware of surrounding vehicles, assist decision making and, ultimately, prevent collisions. The research used a variety of human factors methods to examine the system usability, acceptance and effectiveness. The results of the evaluation identified deficiencies with the proximity detection system and other factors of the operating environment. These produced a number of recommendations. An investigation of a subsequent collision at the site verified many of the issues observed. Some of the interface design recommendations were consequently developed and implemented with positive operator acceptance. The application of human factors methods can lead to positive changes in the design of proximity detection systems and, more broadly, help develop effective mining technologies from a user-centred perspective.
In conclusion, the three studies described in this thesis have produced both practically useful benefits and a contribution to knowledge. The results will encourage more widespread adoption of such human factors techniques by both mining equipment users and designers.