Sensor Network Robustness Using Model-Based Data Reconciliation for Continuous Tablet Manufacturing.

ABSTRACT: Advances in continuous manufacturing in the pharmaceutical industry necessitate reliable process monitoring systems that are capable of handling measurement errors inherent in all sensor technologies and detecting measurement outliers to ensure operational reliability. The purpose of this work was to demonstrate data reconciliation (DR) and gross error detection methods as real-time process management tools to accomplish robust process monitoring. DR mitigates the effects of random measurement errors, while gross error detection identifies nonrandom sensor malfunctions. DR is an established methodology in other industries (i.e., oil and gas) and was recently investigated for use in drug product continuous manufacturing. This work demonstrates the development and implementation of model-bas

SUBMITTER: Moreno M 

PROVIDER: S-EPMC9942238 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature