Models

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Quality Assurance with Ai-Metrix Automated Model Validation

Ai-Metrix Automated Model ValidationAi-Metrix®now offers a fully automated model validation framework, combining real-time tracking with powerful diagnostics based on ASTM D6122 and comprehensive Nelson Rule monitoring. Designed to support high-stakes environments like gasoline blending, this feature ensures your predictive models remain accurate, reliable, and audit-ready as new data flows in.

🎯Smarter Monitoring Starts Here
As your team uploads fresh data to the Ai-Metrix server, our system continuously evaluates model performance using robust statistical tools. A streamlined dashboard gives you instant visibility:

✅ Visual Control Charts – Instantly identify anomalies with trend plots showing ±1, 2, and 3 standard deviations.
✅ Advanced Rule Integration – Choose from Nelson Rules or ASTM D6122 checks to detect early signs of model drift or calibration issues.
✅ Dynamic Model Grid – See all active models at a glance, organized by product grade and property. Click to dive deeper into sample counts and validation metrics.
✅ Flexible Metric Selection – Monitor predicted values, residuals, F-ratios, or Mahalanobis distance to match your validation strategy.
✅ Rule Violations Trigger – Violations can trigger an email to a distribution list for action.

🎯Why It Matters
→ Regulatory Alignment – ASTM D6122 compliance, built-in.
→ Hands-Free Oversight – Continuous, automated validation as data is collected.
→ Proactive Alerts – Catch issues before they affect process quality.
→ Complete Transparency – From calibration sample size to rule violations, everything is traceable and actionable.
→ Real time updates – With the Ai-Metrix calibration power, model updates are available in real time to move the system back into compliance.

🎯Confidence in your models isn’t optional—it’s critical.
Ai-Metrix delivers a smarter, automated approach to model validation that helps your team maintain compliance, ensure process integrity, and make better decisions, faster. Explore the new validation dashboard today and take control of your model quality.

Book a quick demo and see how Ai-Metrix can elevate your operations. info@infometrix.com

“Quality is never an accident. It is always the result of intelligent effort.”
– John Ruskin, English writer (1819-1900)

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Analytically Speaking Podcast Ep. 33 – Automating Chemometrics for Expert Calibration System

Analytically Speaking Podcast Ep. 33 Host Dr. Jerry Workman speaks with Dr. Brian G. Rohrback to discuss to his research and experience in automating the process of building multivariate calibrations.

Enjoy the podcast. For more information and further conversation, contact us at info@infometrix.com.

Click to access Analytically Speaking Podcast Ep.33

 

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Automating the Optimization of Locally Weighted Models is a Solution

Automation of Local Regression Model Building for Spectroscopic Data, JChem2024 Pell et alA calibration model tends to improve as additional calibration samples are added to the library. If the samples reflect variation in the chemical composition, the model then expands its zone of relevance. Ultimately, as these new zones expand calibration scope, the model can degrade in performance due to nonlinearities and may require adding to the model rank, which can make the model fragile. Building local models is one answer to gain the best of both worlds, but optimizing a locally weighted model is tricky and time consuming. Automating the optimization of locally weighted models is a solution.

http://doi.org/10.1002/cem.3637

For additional information or questions, contact info@infometrix.com.

#chemometrics #LWR #spectroscopy #regression

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IFPAC 2025 – Save the Date

IFPAC 2025
Date: March 2-5, 2025
Venue:  Washington, D.C.
website: www.ifpacglobal.org

If you are interested in keeping abreast of the interactions of chemometrics, analytical instrumentation, and data processing (particularly as it relates to the bio and pharma world) this is the place to go.

If you have an interesting application in chemometrics, machine learning, or information architecture, contact us at info@infometrix.com.

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Augmented Models

Picture a situation where a company has a spectrometer and model that is performing well in a quality control setting. The company wants to set up a second spectrometer for another line or another location. Normally, we need to wait until enough spectra and reference values are available to be able to build a competent model, which can take months, even a year. In Ai-Metrix, a customer can choose to jointly model a data-rich spectrometer with a data poor instrument. If Ai-Metrix sees a discrepancy in data amounts, it clicks in a new set of optimization parameters and builds an augmented model that should be available within days. The model will not be as good as a well-populated calibration, but the system would then dial itself in as more data becomes available. Because Ai-Metrix does not care how many models a user creates, the marginal cost for this series of model updates is essentially zero. And you can put the spectrometer to use right away.