Abstract
Coal has been a vital energy source globally and in South Africa. It accounts for 36 % of the energy resources present in forming the world’s electricity. South Africa’s huge coal reserve has made it as the fifth largest coal producer in the world, generating coal at the rate of 224 million tons annually. About 77 % of the South African energy demands are met through coal production and supply. The mined coal from South African mines is supplied to several power stations predominantly owned by Eskom. These power stations utilize the supplied coal for the generation of electricity. Electricity is imperative as it enables the improvement of food production and conservation. To achieve the overall coal production target in South Africa, mechanization and preparation in coal mining is imperative. Several mining machines and equipment are involved in coal mining operations in South Africa.
It has been observed that unexpected failures of the equipment and machines in South Africa mines are still prevalent despite the improvements that have been made on some of the mining equipment over the years. This causes a lot of downtime and consequently leads to loss of cost in the form of maintenance, operation, and logistics. All operations and maintenances in South African mines inevitably involve human efforts. Human errors are bound to happen once human beings form part of any operation. Error is an inevitable consequence of human which impact industries negatively. However, to create a safe, reduced human-induced incident mining environment and to better manage emergency in mining operations in South Africa, it becomes pertinent to create human factors analysis, monitoring and management using an adapted human factor analysis framework.
The motivation for this research is to sensitize on the need to identify, take cognizance and report human-induced error in operation and maintenance of mining equipment. Human-induced errors are often neglected but have caused significance failures, incidents, and downtimes in the machine operation. This dissertation is therefore aimed at understanding the significant contributions and causes of human errors in operation and maintenance of mining equipment. This is achieved through analysis of case studies of failure incidents in some mine machines, in the South African context. Case studies were selected based on their frequency of operations and applications, and its importance in mining operations. Observation and qualitative analysis were used for this dissertation using existing framework relevant to the case studies based on the information relating
v
to operations and maintenance. The quantitative representation of results was adopted to simplify the analysis. The purpose of this analysis was to identify human errors and human error impacts in operation and maintenance of mining equipment.
The result of the analysis revealed that much attention should be given to the hydraulic subsystem in the operation of the LHD owing to its high frequency of failure occurrence. Both electrical and mechanical subsystem of the Bucket wheel excavator have moderate probability of human error traces in its operations, while certain maintenance-related human error is caused by carelessness, inexperience, neglect of danger in its certain maintenance operations. Lack of training has been identified as a prominent cause of human error in maintenance of the bucket wheel excavator. The frequency of maintenance-related failure of the dragline accounts for the largest share of total failure frequencies. This dissertation identified a knowledge-based skill factor to account as the largest factor of human errors in the mining vicinity. It is followed by unsafe acts tiers with physical environment as the major precondition to the unsafe acts.
This research has revealed the significant contributions of human error in the failure of mine machines despite their neglect. This research should help the concerned sectors to identify the need to adequately report, monitor and assess human error in operations and maintenance of the mine machines and how to better manage them. Several solutions which may likely prove effective on the causes of human errors that result in failure incidence and accidents in mining operation are proposed in this research study. The results of this dissertation will be beneficial as a convenient industrial-based tool for human-induced error analysis of failure. Even though the framework was modified and adapted to mining case studies, it also finds practical application in other high-risk operations like manufacturing companies. This is because this report has highlighted a few solutions and ways in which human friendly machines can be manufactured, to reduce human errors in operation and maintenance.
Keywords: Human error; human factor; incidents; mines; maintenance; operation.