Leveraging AI for Flawless Production :  Quality Control in Pharmaceutical Manufacturing

Let’s have AI solve our quality challenges, it worked in the demo, right? AI requires very different thinking vs traditional mechatronic and software systems, especially in keeping its running costs in check. This talk will walk through some less intuitive pitfalls with AI for quality assurance and look into some future trends that further improve the feasibility of this long-running AI promise for higher quality at lower cost.

Content

Author and article information

Conference

Publisher: REPO4EU

Publication date (Electronic, pub): 6 June 2024

Affiliations

[1 ] Silo AI, Finland;

[2 ] Silo AI Netherlands, The Netherlands;

Author notes

[* ]Email: niko.vuokko@ 123456silo.ai .

Author information

Bart Gips https://orcid.org/0000-0003-3392-216X

Ali Bahramisharif https://orcid.org/0000-0002-2593-2686

Article

DOI: 10.58647/REXPO.24009

SO-VID: 1b5952be-608e-4ace-95a7-72fa0648a06c

License:

Published under Creative Commons Attribution 4.0 International ( CC BY 4.0). Users are allowed to share (copy and redistribute the material in any medium or format) and adapt (remix, transform, and build upon the material for any purpose, even commercially), as long as the authors and the publisher are explicitly identified and properly acknowledged as the original source.

Conference name: RExPO24

Conference number: 3

Conference location: Munich, Germany

Conference date: 3-5 July 2024

History

Product

REPO4EU

Data availability: Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

Keywords: AI for Quality Assurance (QA),Hidden Costs of AI in QA,Future Trends in AI-powered QA

Leveraging AI for Flawless Production : Quality Control in Pharmaceutical Manufacturing

Abstract