Aniline reactor predictive maintenance

Company

NDA

Industry

Chemical Manufacturing

Country of the Company

NDA

Type of Service

Consulting

Tasks

  • Optimize data acquisition from multiple real-time sensors monitoring the aniline synthesis process.
  • Develop a Deep Learning algorithm to detect reactor issues using multisensor data.

Challenges

Key challenges included integrating real-time multisensor data, managing process variability, and developing a reliable AI model with limited failure data for accurate reactor issue detection.

Solutions

  • A complex Neural Network model was developed to perform sensor data fusion and predict reactor hard stop.

Outcomes

  • The developed Neural Network model introduced additional control capabilities and improved process visibility, resulting in a 40% reduction in reactor failures.

Technologies Used

PyTorch

LSTM

CNN

COMPANY

NDA

Industry

Chemical Manufacturing

Country of the Company

NDA

Type of Service

Consulting

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