Work

Artificial intelligence applications for fault detection and diagnosis in pharmaceutical bioprocesses: a review

Year: 2024

Type: review

Abstract: Because of increasing demand and strict regulations, pharmaceutical manufacturers encounter significant hurdles in achieving high productivity while ensuring normal process states. Variability in raw materials and operational disturbances can lead to deviations from normal operating conditions that result in decreased productivity. The implementation of smart fault detection and diagnosis (FDD) techniques is crucial for attaining acceptable productivity and ensuring process safety. In this review, we identify the major challenges of smart FDD in pharmaceutical processes, and we discuss future opportunities and new perspectives.

Source: Current Opinion in Chemical Engineering

DOI: 10.1016/j.coche.2024.101025

Authors: Mohammad Aghaee, Abhishek Mishra, Stephane Krau, Ibrahim Melih Tamer, Hector Budman

Institutions: University of Waterloo, Sanofi (Canada)

Language: English

Topic: Fault Detection and Control Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $4,130

Funders: Mitacs, Sanofi Pasteur