Industry events where we will be featured

March 20 9:00AM – Data Driven Models and AI Session – Room 202

Abstract: Thermal spray practitioners have long struggled to define robust process windows—combinations of particle temperature, velocity, and plume intensity that reliably yield acceptable coatings—especially as powder characteristics, equipment wear, and ambient conditions evolve. The Accuraspray HUB addresses this challenge by unifying data capture, structuring, and analysis within a single platform. During an initial lab deployment, the Hub continuously collects summary statistics (mean temperature, velocity, and intensity) for each spray run and automatically enriches them with detailed metadata—stand-off distance, gas and powder flow rates, powder batch IDs, gun maintenance records, and environmental measurements. These per-run feature vectors are then subjected to density-based clustering (K-means, DBSCAN, HDBSCAN) to identify the natural “normal” operating regimes without requiring explicit “bad coating” examples. From the resulting high-confidence clusters, the Hub derives multidimensional min–max envelopes that define process windows tailored to specific powders and gun health states. By delivering reproducible data pipelines, transparent feature engineering, and modular analytics, the Accuraspray HUB not only accelerates the discovery of stable operating conditions—but also bridges the longstanding divide between thermal spray experts and the machine learning community, paving the way for scalable, data-driven process control.