AI-Driven Predictive Maintenance System for Mining Equipment

In the high-stakes industry of mining and extraction, equipment downtime can result in significant operational losses. Our enterprise seeks to implement an AI-driven predictive maintenance system that leverages the latest advancements in AI and machine learning to predict equipment failures before they occur. Utilizing LLMs, computer vision, and predictive analytics, the system will analyze data from sensors and operational logs to identify patterns and potential points of failure. The solution will integrate technologies such as OpenAI API, TensorFlow, and PyTorch for robust machine learning model development, while Langchain and Pinecone will support data processing and management. By predicting maintenance needs, the system aims to reduce unplanned downtime and maintenance costs, ultimately enhancing the productivity and profitability of mining operations. The project will be executed over 16-24 weeks, allowing for comprehensive testing and implementation across various mining sites.