In refining and petrochemical industries, optimizing production processes is critical to improving product yields and minimizing operational costs. Digital twins, virtual representations of physical processes linked to real-time data, enable continuous optimization and dynamic decision-making. These models offer insights into current operations, predict future outcomes, and suggest optimal strategies for both short- and long-term operations.
The integration of process simulation, data-driven models, and real-time optimization within a unified framework provides a powerful tool for refining and petrochemical operators to make more informed decisions, mitigate risks, and adapt to changing operational conditions.
