A digital twin framework to support vehicle interaction risk management in the mining industry

• Published in: MATEC Web of Conferences
• Main Authors: Verster Jaco, Roux Pieter, Magweregwede Fleckson, de Ronde Willis, Crafford Gerrie, Mashaba Musa, Turundu Safiya, Mpofu Mvikeli, Prinsloo Jacobus, Ferreira Pieta, Brodner Hartmut
• Format: Article in Journal/Newspaper
• Language: English; French
• Published: EDP Sciences 2023
• Subjects: Engineering (General). Civil engineering (General); TA1-2040; sami
• Online Access: https://doi.org/10.1051/matecconf/202338811002; https://doaj.org/article/04f21998c9ae47119d89433fe387aa00

In recent years, transport-related accidents, notably those involving trackless mobile machinery (TMM), have consistently ranked among the top three causes of fatalities and injuries in the South African mining industry (SAMI) [1]. These accidents arise from a combination of mechanical and technical malfunctions, environmental factors, and human or machine operator errors. Remarkably, these incidents persist despite the existence of specific regulations, standards, and codes of practice for transportation and machinery. This paper introduces a digital twin framework for TMM, which employs a systems engineering approach combined with software tools and computational analysis. This framework aims to enhance the current regulations by offering a continuous, quantitative risk assessment. By modelling and detecting non-conformance and adverse vehicle interaction events, the framework provides a quantitative risk analysis that complements the prevailing qualitative methods reliant on historical data and operational experience. A case study conducted at the CSIR main campus in Pretoria showcases the potential of the TMM Digital Twin.