Solution

The plant used Aleph AI Co-Pilot platform to develop a digital twin of the distillation process, modelling the thermodynamic properties and multi-component feeds. Subsequently, Aleph AI diagnosed the causes of fluctuating energy profiles and constantly recommended corrective actions to achieve optimal energy efficiency.

Outcome

Causes of the initial issue identified on reflux ratio, bottom product flow rate, and reboiler duty. With Aleph AI, the plant has been able to reduce 33% of energy consumption per unit product.

Solution

The plant used Aleph AI Co-Pilot platform to monitor, diagnose, and alert deviation in the moisture content. Subsequently, the Co-Pilot system has been constantly supporting the operators by recommending corrective actions to achieve the desired moisture content.

Outcome

Causes of the initial issue identified on heat exchanger, ambient temperature, and recycle moisture carryover. Aleph AI Co-Pilot has assisted the plant to constantly achieve the desired moisture content; thus, improving product quality by 35%.

Solution

The plant implemented Aleph’s AI Co-Pilot platform to monitor viscosity targets in real-time and continuously supports operators by recommending adjustments in raw material feed rate and mixing parameters to maximise specific yield without compromising viscosity standards.

Outcome

Aleph AI Co-Pilot identified that manual, conservative raw material additions at each stage were the main cause of inefficiencies. With AI-driven recommendations, the plant consistently achieves optimal product quality with lower raw material consumption, resulting in a 21-29% improvement in specific yield.