Overcome your biggest process tuning time bottlenecks
Leverage your data for faster, more efficient, cost-effective, and optimal quality control that accurately predicts performance.
Fine-tuned process calibration through machine learning
Spend less on technical support and machine costs
Increase throughput and reduce cycle time to seconds
Gain deep insights into product quality
Use predictive analytics to ensure the best yield
Calibration and quality control stations are time-consuming, expensive, and avoidable.
Quality control stations are a crucial step between manufacturing processes, but they can often feel more like a stopping point. In addition to being time-consuming and expensive, they frequently only cover a small sample of a batch’s manufactured volume.
They’re imperfect, but they don’t need to be. You already know how much data is generated by manufacturing. Why not use that?
Through Process Tuning Time Optimization, manufacturing data can be used to predict performance values or vectors instead of quality control stations, speed up calibration, determine the optimal configuration for each process, and stop unnecessary processes early.
Seagate Accelerates Anomaly Detection Solution Scaling and Democratizes Machine Learning Discover how Seagate’s partnership with Vanti enables a path to scaling an anomaly detection solution across 100+ operations, and democratize this process beyond the data science team.
Data-driven efficiency across
the manufacturing process
Save valuable time spent on calibration stations through predictive analytics.
Simplified integration with your existing data sources
Spend less time on configuration with a solution that’s integration-ready with the most popular data storage solutions.
Drive business value from calibration data
Optimize tuning parameters for more efficient, cost-effective manufacturing.
Discover faulty units early in the manufacturing process
See how your data can improve early fault detection faster