(38b) Next Generation Process Modelling Utilizing Digital Twins

Making timely and effective process scheduling and operational decisions, within an environment of constant change, is a key success factor in today's dynamic market. With recent technology advances, legacy simulation modelling tools are being replaced with state-of-the-art process simulation suites, where one model and one platform services multiple purposes. Not only faster and more reliable, the next generation refining and petrochemical modelling platform can solve complex problems, without the need for a "what-if" trial and error approach.

A next generation process modelling platform is designed to be generally applicable to any modelling need, without requiring extremely specialized skills to develop and maintain. An open platform useable by anyone to express their domain knowledge without specialized programming skills. A platform where the direct application of rigorous mathematical optimization capability can help calibrate a digital twin model and be used to explore a rigorous model decision space.

This digital twin model on an optimization platform provides a simultaneous solution technique to reduce maintenance costs, increase plant utilization, maximize plant performance via energy reduction, quality giveaway minimization and/or yield improvements, and create fast and accurate analytical derivatives for integration with external optimization, planning and scheduling applications to enhance the business portfolio, capturing opportunities in the global markets. All of this is accomplished with a computationally fast “warm start” capability to track and compare model and plant operations in real time. It has been predicted that by 2021, half of large industrial companies will use digital twins, resulting in those organizations gaining a 10% improvement in effectiveness.[1]

This paper presents the use of UniSim Design for real time refining and petrochemical modelling via Digital Twin applications, which supports a faster decision-making process for plant optimization and reliability improvement programs.

[1] https://www.gartner.com/smarterwithgartner/prepare-for-the-impact-of-dig...