Process Analytical Technology -Chemometrics

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Spectroscopy Method Development

Coming Soon

• Design the Process: Develop a process that integrates spectroscopy and chemometrics techniques for monitoring and analyzing the process.
• Select Spectroscopic Techniques: Choose appropriate spectroscopy methods (e.g., NIR, UV-Vis, SoloVPE, Raman, Terahertz, FTIR etc) based on application.
• Develop Chemometric Models: Create and validate chemometric models to interpret spectroscopic data (e.g., PCA, PLS, ANN, AI, ML).

• Data Acquisition: Implement systems to collect real-time spectroscopic data from the process.
• Data Integration: Ensure the data is integrated with chemometric models for analysis.

• Critical Quality Attributes (CQAs): Define and monitor CQAs in real-time using the spectroscopic and chemometric data.
• Visualization: Use dashboards or visualization tools to display real-time data and predictions.
• Predictive Analysis: Apply chemometric models to predict outcomes and trends based on real-time data.

• Select Control Charts: Choose appropriate control charts for monitoring process stability (e.g., X-bar, R charts).
• Plot Control Charts: Regularly plot data points and control limits on charts.
• Real-Time Analysis: Continuously analyze control charts to identify deviations or trends.

• Process Control: Implement control strategies based on chemometric analysis to adjust process parameters.
• Feedback Loop: Create a feedback mechanism to update chemometric models and process controls based on new data and observations.

• Delta-V Analysis: Monitor changes and deviations (Delta-V) in real-time to ensure process stability.
• Data Historian: Use data historians to store historical process data for long-term analysis and trend identification.
• Documentation: Keep comprehensive records of data, analyses, and changes made to the process.
• Communication: Regularly update stakeholders with findings and improvements.

Coming Soon