(590d) Enabling Bioprocess Development Using Virtual Plant Technology
AIChE Annual Meeting
Wednesday, November 11, 2015 - 4:12pm to 4:31pm
Dynamic process modeling is a valuable tool for understanding process behavior and testing new ideas in a safe and secure environment. It can be used to identify and test new operating conditions, process configurations, control strategies, or operating procedures that increase yield, reduce costs, or impact any other important performance indicator. Dynamic models can also be extended in order to train new and existing operators on unusual or emergency conditions, reducing operator error, improving operational consistency, and making hazardous processes inherently safer to run. DuPont™ TMODS, a proprietary dynamic modeling software package developed and maintained by the Dynamic Simulation, Control, and Optimization Group in DuPont Engineering Research and Technology (DuET), is by far the most commonly used dynamic simulation tool in DuPont. As such, the modeling capability in DuPont™ TMODS is highly leverageable, and the tool has very broad use and acceptance across DuPont.
Over the last several years, DuPont has made a clear, long-term commitment to developing and operating bioprocesses. Enabling the DuPont strategic direction in biotechnology depends on Virtual Plant Technology. Virtual Plant Technology refers to the application of dynamic modeling to address the needs of the project development cycle, including evaluation and testing of process alternatives, operability studies, control structure design and testing, DCS configuration testing, and operator training. Dynamic modeling and simulation are often more critical in bioprocess development, where complex flowsheets make extensive use of batch or combined batch / continuous processing. Plant-wide batch automation is challenging, requiring synchronization of different batch unit operations, arbitration of shared equipment, and coordination with the continuous processing units, while maintaining the operating conditions at their target and within constraints. Further, steady state process models are typically incapable of accurately determining variability and maximum or minimum loads on equipment and utilities. Therefore, dynamic simulation is an important tool to understand the inherently complex dynamic behavior of the integrated bioprocess and develop automation and process control strategies that optimize performance, which translates into better design, operating policies and understanding of constraints, and process control, and opens the door for significant financial benefits.
DuPont™ TMODS and dynamic modeling are key components of Virtual Plant Technology as practiced in DuPont. For the last two decades, Virtual Plant Technology has been used throughout DuPont’s chemical and polymer businesses to improve process understanding and make processes more profitable. In recent years, DuPont engineers have enhanced Virtual Plant Technology to include more capability relevant to bioprocessing. These new capabilities include bioreactions (e.g. aerobic and anaerobic fermentation), bioreactors like bubble columns and aerated stirred tank fermenters, and relevant types of solid-liquid separations. Furthermore, because many bioprocesses are batch or a mixture of batch and continuous operations, batch sequencing and automation have also been updated. This talk will focus on how Virtual Plant Technology is being used in DuPont to support the development of bioprocesses. For example, it has been used to study process alternatives, such as the effect of different bioreactor designs or the use of perfusion and cell recycle, and to support the process economic evaluation of those alternatives. It has also been used to develop control strategies and study process operability, leading to important changes in process design. Virtual Plant Technology has also played a vital role in bioprocess commercialization, including operator training simulators, control system functional description development, and control system configuration and checkout.
This paper has an Extended Abstract file available; you must purchase the conference proceedings to access it.
Do you already own this?
Log In for instructions on accessing this content.
|AIChE Pro Members||$150.00|
|AIChE Graduate Student Members||Free|
|AIChE Undergraduate Student Members||Free|
|AIChE Explorer Members||$225.00|