Life sciences manufacturers are faced with quality anomalies that can delay product release for hundreds of hours. Often, quality management systems rely on manual processes for data transfer. This proves to be inefficient, hinders visibility, creates data integrity concerns and causes lengthy delays. Additionally, despite the growing application of continuous process verification, many such programs don’t use real-time automation data for verification which limits quality by design (QbD) value, increases compliance risk and threatens supply chain continuity.
The key benefits of enabling QbD with AI-driven quality operations include:
• Connecting AI-enabled quality management and batch automation to provide real-time visibility
• Using real-time critical process parameter alerts to provide early detection
• Enabling proactive response to quality events through manufacturing anomaly capture
• Improving cost of poor quality without increasing the cost of good quality
QbD is enormously valuable and generates a lot of data and knowledge. Unfortunately, it tends to be underutilized, siloed and not operationalized. It is too often an exercise, executed at the early stages of product development but was always intended to be dynamic, increasing its value across the lifecycle of a product. Honeywell functionality is changing that.
Download Whitepaper
* Your information is safe with us. We hate SPAM too.