Automation Technologies to Enable Data-Rich Experimentation: Beyond Design of Experiments for Process Modeling in Late-Stage Process Development
Jon A. Jurica, Jonathan P. McMullen
Abstract
Automated reactor and sampling technologies were used in process characterization studies of a cyclization reaction using gaseous ammonia. These data-rich experiments were structured according to a 24 full factorial design of experiment, with each experiment having 12 reaction samples at equal time intervals. Data-driven models were established for key reaction responses to create a process fingerprint, to identify the optimal operating conditions under various constraints, and to evaluate the stability of the process. Leveraging these technologies in late-stage reaction characterization enabled significant improvements in efficiency and experimental reproducibility compared to conventional methods.
Topics & Concepts
Process (computing)Computer scienceAutomationProcess engineeringDesign of experimentsAdvanced process controlProcess controlSampling (signal processing)EngineeringMathematicsMechanical engineeringComputer visionOperating systemFilter (signal processing)StatisticsInnovative Microfluidic and Catalytic Techniques InnovationAnalytical Chemistry and ChromatographyMicrofluidic and Capillary Electrophoresis Applications