Meet Our Experts at IFPAC 2022
May 16, 2022
Manufacturing Intelligence at the Forefront
IFPAC continues to set precedence as a forum for insightful discussions bringing you the latest trends and real-life applications in the fields of Quality by Design, Process Analytical Technology, Quality Metrics, Continuous Manufacturing and Process Control applications for the pharmaceutical, biotechnology, generic, chemical, petrochemical, food, and related industries. Our Continua Process Systems subsidiary and Emerson will be there to join our colleagues at IFPAC-2022 to share and discuss our latest progress in Continuous Manufacturing, PAT, Process Control and Data Analytics.
Case Study: RTD Models Tracking Material Concentrations and Lot Genealogy for a Continuous Manufacturing CDC Line
Results of Residence Time Distribution model performance testing on a Direct Compression, Continuous Manufacturing line will be presented for a setup with 3 feeders, a blender, and tablet press and compared with parallel and redundant PAT model data. The system-generated data are stored in an SQL database and used to produce reports that track tablet concentrations and raw material lot genealogy on a second-by-second basis with a high degree of accuracy.
MTP File Development Demo of a ‘Plug And Play' Interface To Support Flexible Manufacturing for a Solid Dose Feeder
A NAMUR compliant MTP file prototype for a Coperion K-Tron feeder (PEA) will be demonstrated that can be imported to a POL through a 3rd party MTP wizard. The POL code is autogenerated based on the MTP file specifications. The MTP file was created using an AML software utility for the XML style format file. For real time communications between the POL and PEA, an OPC UA server was developed using Python and runs on a Raspberry PI.
Applying Machine Learning Algorithms To Continuous Manufacturing for Continuous Process Improvement
Multi-variate models such as MSPC-PCA and PLS built and tested on a direct compression Digital Twin will be demonstrated. These statistical models are used to detect variation and faults and to optimize the process, reduce plant variation, and increase product quality. A specific example will demonstrate a feeder model that predicts product density and its impact on tablet properties such as hardness and weight.