EAM solutions driven by GenAI help save mining maintenance expenditures, increase fleet availability, and optimize inventory and technician efficiency, making the process smarter.

The maintenance needs of mines have risen globally, with the unwarranted maintenance constituting the larger proportion of the total mine maintenance cost, but generative AI (GenAI) is one answer to this problem. In six months, Boston Consulting Group (BCG) reports that the appropriate GenAI tools can reduce the costs of maintenance by 10% and increase the availability of a fleet by 15%.

Unlike traditional predictive maintenance, GenAI uses both unstructured and structured data to provide intelligent diagnostics, make parts ordering easier in real-time, and support technicians in the field. Its orchestration features enable the mining corporations to derive a pattern using various tricks of data, leading to efficiency and less downtime.

Importantly, GenAI is showing its value in combination with Enterprise Asset Management (EAM) systems. Modular GenAI solutions on top of the existing EAM systems can help even the mining facilities with less digital maturity. This combination ties in the forecast of asset health to an inventory and supplier schedule to guarantee proper parts at the proper time.

Field technicians are also the winners. BCG Platinion has created GenAI-based conversational agents that can interpret complex fault codes into practical measures to increase safety and reduce human error. GenAI ensures that workflows are optimized (since learning is embedded into operationalization) and tackles the talent issues that the mining industry is facing.

Having flawless connectivity with ERP/EAM/OT systems, BCG observes that mining businesses are actually seeing remarkable returns in terms of performance. As independent coordination becomes the new frontier, GenAI will transform maintenance into predictive and eventually, autonomous.