Artificial intelligence, machine learning, and autonomous technologies in mining industry

• Main Authors: HYDER, Zeshan, SIAU, Keng, NAH, Fiona
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Artificial Intelligence; Autonomous Technology; Autonomous Trucks; Challenges of AI and Machine Learning; Machine Learning; Mining Industry; Artificial Intelligence and Robotics; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/9530; https://ink.library.smu.edu.sg/context/sis_research/article/10530/viewcontent/AI_ML_2019_JDM302_pv.pdf
• Institution: Singapore Management University

The implementation of artificial intelligence (AI), machine learning, and autonomous technologies in the mining industry started about a decade ago with autonomous trucks. Artificial intelligence, machine learning, and autonomous technologies provide many economic benefits for the mining industry through cost reduction, efficiency, and improving productivity, reducing exposure of workers to hazardous conditions, continuous production, and improved safety. However, the implementation of these technologies has faced economic, financial, technological, workforce, and social challenges. This article discusses the current status of AI, machine learning, and autonomous technologies implementation in the mining industry and highlights potential areas of future application. The article presents the results of interviews with some of the stakeholders in the industry and what their perceptions are about the threats, challenges, benefits, and potential impacts of these advanced technologies. The article also presents their views on the future of these technologies and what are some of the steps needed for successful implementation of these technologies in this sector.