Part I shone a spotlight on the current state of industry disruption, hidden costs, industry learnings and regulatory framework support. Adding to the topic of digital transformation and technology solutions, predictive maintenance can also be a valuable quality control (QC) asset.
Supervised learning, a subfield of machine learning in which algorithms are trained on labelled datasets, is used for predictive maintenance and QC in healthcare manufacturing.
When trained on manufacturing process, equipment sensor or quality test data, the model can learn to forecast process abnormalities, equipment breakdowns or product quality deviations.
Generative AI can help companies to redesign their end-to-end deviation investigations and management processes by providing tools that facilitate explaining trends, severity of deviations, potential root causes and corresponding corrective actions.
All required reports can automatically be created and reviewed in accordance with corporate quality procedures.
Not yet a Subscriber?
This is a small extract of the full article which is available ONLY to premium content subscribers. Click below to get premium content on Manufacturing Chemist.
Subscribe now Already a subscriber? Sign in here.