Amponsah-Dacosta, F.Mhlongo, Sphiwe EmmanuelMasindi, Masala Theron2023-11-172023-11-172023-10-05Masindi, M. T. (2023). Analysis of work accidents data: A case study of the South African mining industry. University of Venda, Thohoyandou, South Africa.<http://hdl.handle.net/11602/2653>.http://hdl.handle.net/11602/2653MESMEGDepartment of Earth SciencesFor any industry to be successful, its production needs must be met while the highest safety standards are maintained. Mining accidents and their subsequent fatalities have enormous social and economic consequences. The current study was undertaken to better understand the fundamental causes of mine accidents so that major remedial actions can be developed and implemented to improve safety in the mining industry. The purpose of this study was to analyse work accident data of the South African industry that was compiled for the period 2008–2017. Secondary data on accidents was requested from the Department of Mineral and Energy Resources (DMRE). Accident data obtained from DMR was summarized, characterized, and described in a meaningful manner to determine the variables or factors which contribute to accidents in the mining industry. Variables that contribute to accidents in the mining includes fall of ground/rock fall, machinery, transportation and mining, general, conveyance accidents, electricity, fires, explosive, heat sickness and miscellaneous. Descriptive statistics, figures, and tables were used to describe and understand the accidents within the mining industry. A chi-square test was used to quantify the extent to which accident outcomes and commodities are independent of each other by year and injury type. This was done to examine the association between the dependent accident outcome and the independent variables such as year, commodity type, and casualty type. The study was significant in that its findings will contribute to building a culture of safety within the mining environment1, which was not only to reduce the risks of miners being exposed to potential workplace accidents but also had an impact on their attitude and perceptions towards workplace safety and their perception of zero as this is one of the priorities which the mining industries need to achieve. The study produced results that summarize the influence of year, commodity type, and casualty type on accident outcome. In particular, the analysis of accidents helped in establishing the relationship between the dependent accident outcome variable and several independent variables, such as year, commodity type, and casualty type, there was an increased number of accidents with respect to different commodities with different in years. The findings of this study vi will be used in planning, designing, and implementing health and safety programmes that will contribute to decrease in the number of accidents for mining different commodities in South Africa. Keywords: mining accidents, accidents data1 online resource (xi, 67 leaves) : color illustrations, color mapsenMining accidentsUCTDAccidents data analysisFatalitiesChi-Square testDissertationMasindi MT. Analysis of work accidents data: A case study of the South African mining industry. []. , 2023 [cited yyyy month dd]. Available from: http://hdl.handle.net/11602/2653Masindi, M. T. (2023). <i>Analysis of work accidents data: A case study of the South African mining industry</i>. (). . Retrieved from http://hdl.handle.net/11602/2653Masindi, Masala Theron. <i>"Analysis of work accidents data: A case study of the South African mining industry."</i> ., , 2023. http://hdl.handle.net/11602/2653TY - Dissertation AU - Masindi, Masala Theron AB - For any industry to be successful, its production needs must be met while the highest safety standards are maintained. Mining accidents and their subsequent fatalities have enormous social and economic consequences. The current study was undertaken to better understand the fundamental causes of mine accidents so that major remedial actions can be developed and implemented to improve safety in the mining industry. The purpose of this study was to analyse work accident data of the South African industry that was compiled for the period 2008–2017. Secondary data on accidents was requested from the Department of Mineral and Energy Resources (DMRE). Accident data obtained from DMR was summarized, characterized, and described in a meaningful manner to determine the variables or factors which contribute to accidents in the mining industry. Variables that contribute to accidents in the mining includes fall of ground/rock fall, machinery, transportation and mining, general, conveyance accidents, electricity, fires, explosive, heat sickness and miscellaneous. Descriptive statistics, figures, and tables were used to describe and understand the accidents within the mining industry. A chi-square test was used to quantify the extent to which accident outcomes and commodities are independent of each other by year and injury type. This was done to examine the association between the dependent accident outcome and the independent variables such as year, commodity type, and casualty type. The study was significant in that its findings will contribute to building a culture of safety within the mining environment1, which was not only to reduce the risks of miners being exposed to potential workplace accidents but also had an impact on their attitude and perceptions towards workplace safety and their perception of zero as this is one of the priorities which the mining industries need to achieve. The study produced results that summarize the influence of year, commodity type, and casualty type on accident outcome. In particular, the analysis of accidents helped in establishing the relationship between the dependent accident outcome variable and several independent variables, such as year, commodity type, and casualty type, there was an increased number of accidents with respect to different commodities with different in years. The findings of this study vi will be used in planning, designing, and implementing health and safety programmes that will contribute to decrease in the number of accidents for mining different commodities in South Africa. Keywords: mining accidents, accidents data DA - 2023-10-05 DB - ResearchSpace DP - Univen KW - Mining accidents KW - Accidents data analysis KW - Fatalities KW - Chi-Square test LK - https://univendspace.univen.ac.za PY - 2023 T1 - Analysis of work accidents data: A case study of the South African mining industry TI - Analysis of work accidents data: A case study of the South African mining industry UR - http://hdl.handle.net/11602/2653 ER -