Abstract
Mine water treatment plants (MWTPs) are never operated at optimal conditions. Many well-designed plants still have some non-compliance events. Operators often have an uneven understanding of the process or are not invested in the performance of the MWTP. While there are some very good operators currently working, these are subject to turnover and retirement.
All MWTPs could improve on final effluent quality, reagent consumption, energy consumption, reliability, sludge density, and overall costs. The solution is to integrate artificial intelligence (AI) into the control of MWTPs. Full-scale applications of AI in the chemical processes of mining are still rare. The level of complexity of MWTPs and the current state of AI make it a perfect fit for AI integration in mining. This is a solution that will happen eventually but could be done now and represent an inroads into mining and eventually the processes related to concentrators and smelters, which are more complex. This presentation will describe the needs and steps required to integrate AI in MWTPs.