Oil refinery predicts and prevents pump failures

Two critical oil pumps at the client's refinery experienced recurring seal leakage at unpredictable intervals. If both pumps failed simultaneously, the entire refining section would require emergency shutdown, resulting in significant production losses and revenue impact. The existing monitoring approach lacked predictive capabilities, forcing reactive maintenance decisions that massively increased operational risk and costs.

Hifiylabs developed a real-time monitoring and predictive solution using machine learning. The model analyzes data from over 40 sensors throughout the refining block to assess system state and predict time until pump failure. Operating times are continuously monitored, with remaining operational time calculated and displayed for engineers in real-time. The solution leverages industrial sensors external to the pump's own system, making the model robust against pump operational states and ensuring reliable predictions.