In this session we will discuss in detail the continuous improvement in plant profitability achieved by having a holistic approach for advanced automation where applications such as procedural automation, Artificial Intelligence Plant Control (AIPC), control strategy in distributed control system and safety instrumented system all work together in harmony. AIPC, leveraging Reinforcement Learning (RL), offers a transformative approach to process plant optimization, addressing key limitations of traditional Model Predictive Control (MPC).

While MPC has been a cornerstone of advanced process control for decades, its reliance on linear models and manual tuning often struggles to effectively handle complex, nonlinear process dynamics, particularly in scenarios with frequent disturbances or changing operating conditions. AIPC overcomes these limitations by continuously learning and adapting to the plant's behavior. We will share our motivation to develop this product in-house and how easy it is to maintain the application and sustain the benefits by existing operations staff without the need of any AI or MPC expertise.

Participants will:

• Understand the benefits of using AIPC over conventional MPC


• Learn how Linde has successfully implemented AIPC on their Air Separation Units that include cryogenic distillation and very complex heat integration and recovery process.


• Realize the importance of embracing this cutting-edge technology for improving profitability and safety of their plant and also for their personal and professional growth.

Moderator:
Atique Malik, AIControl LLC

Presenters:
Rajeev Limaye, Linde Advanced Operations Services
Lena Tetampel, Linde Engineering Munich Germany