Aniline reactor predictive maitanance

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

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