BLT-PrintInsight Launched to Advance Metal 3D Printing Quality Control
Metal 3D printing is revolutionizing manufacturing, especially in high-value sectors such as aerospace, yet persistent defects and quality risks remain major hurdles. At Formnext 2025, BLT unveiled BLT-PrintInsight, a cutting-edge software solution designed to address these challenges by delivering comprehensive, data-driven quality management across the entire printing lifecycle.
Intelligent Quality Management for PBF-LB/M Processes
Targeted at powder bed fusion laser-based metal (PBF-LB/M) printing, BLT-PrintInsight combines online monitoring with offline analysis, enabling full visibility, control, and traceability throughout the production process. By integrating multi-source data fusion with AI-powered analysis, the system provides real-time defect detection, immediate feedback, and post-process risk assessment—offering an end-to-end approach to 3D printing quality assurance.
Data-Driven Insights for Smarter Manufacturing
BLT-PrintInsight collects live process data through its online monitoring module while performing deep, intelligent diagnostics offline. This dual approach allows manufacturers to continuously improve processes, optimize machine performance, and implement a robust, data-driven quality framework—ultimately producing higher-quality parts faster and with greater confidence.
Online Monitoring: Real-Time Visibility and Intelligent Control
The online monitoring module automates defect detection and correction using advanced vision algorithms, reducing manual intervention and improving accuracy. Its key capabilities include:
Powder Spreading Monitoring: Inspects powder bed quality in real time, detecting defects such as uneven spreading, powder shortages, collapse, or recoater collisions, and automatically correcting issues to prevent defects before they propagate.
Scanning Monitoring: Monitors laser scanning quality in real time, identifying burnt spots, slag buildup, and other anomalies, while issuing immediate alerts for operator intervention.
Offline Analysis: In-Depth Traceability and Process Optimization
The offline analysis module provides a comprehensive post-print evaluation, helping manufacturers optimize processes and manage risks with precision. Key features include:
3D Model Visualization: Uses reverse modeling to create digital twins of printed parts, mapping AI-identified defects directly for intuitive visualization of risk distribution.
Defect Record Management: Allows users to rate defect severity, manage defect lists, adjust detection sensitivity, and submit abnormal samples to continuously refine AI detection models.
Multi-Source Data Fusion Dashboard: Aligns printing parameters, environmental data, machine status, and visual images for a holistic view of production. Its one-click anomaly tracing feature identifies defect origins quickly, addressing issues of fragmented data and delayed assessments.
One-Click Quality Reports: Automatically generates reports detailing defect locations, types, risk levels, and associated images, ensuring transparent traceability and evidence-based quality assurance for customers.
Flexible Packages for Diverse Applications
BLT-PrintInsight offers three professional add-on packages to meet varying industry needs:
Defect Self-Training Platform – Enables users to customize AI detection models with their own defect samples.
Near-Infrared Melt Pool Monitoring – Captures thermal radiation signals in real time to produce thermographic maps for precise detection of overheating or lack of fusion.
Video Monitoring – Records the complete printing process, supporting playback and automated cleanup.
BLT-PrintInsight positions itself as a transformative solution for manufacturers seeking full-process control, traceable quality, and data-driven insights in metal additive manufacturing.
For more information: www.xa-blt.com
