Predictive Maintenance Optimization in Chemical Manufacturing Using AI & Machine Learning

Our chemical manufacturing facility is seeking to transition from reactive to predictive maintenance to minimize equipment downtime and maintenance expenses. Currently, unexpected equipment failures result in significant production delays and increased operational costs. We are looking for a skilled AI and Machine Learning expert to develop a predictive maintenance system that can accurately predict equipment malfunctions before they occur. The solution should utilize state-of-the-art technologies such as LLMs, Computer Vision, and Predictive Analytics, with key technologies including OpenAI API, TensorFlow, PyTorch, YOLO, and Langchain. By analyzing real-time operational data from various machinery and employing predictive models, this system will forecast equipment failures, allowing for timely interventions. This project is critical for maintaining production efficiency, ensuring safety compliance, and reducing overall maintenance costs. The successful applicant will have a strong background in machine learning and prior experience in deploying predictive maintenance solutions in an industrial context.