Case Study: Authentise & Addiguru - Advancing Quality Control in Additive Manufacturing

By combining real-time AI defect detection with part-level traceability, Authentise and Addiguru move additive manufacturing quality control from reactive inspection to proactive process control.

The partnership between Authentise and Addiguru represents a significant leap forward in AM quality control. By integrating Addiguru's advanced AI-driven monitoring solutions into Authentise's workflow automation platform, manufacturers gain deeper insights, real-time defect detection, and streamlined operations.

Overview

What We Have Achieved:

• Integrated Addiguru’s AI-driven defect monitoring into Authentise’s MES.

• Enabled real-time defect detection, reducing waste and improving efficiency.

• Provided part-level traceability to link defects directly to corrective process control.

• Created a unified interface for seamless production and quality data integration.

• Successfully deployed the system at i3DMFG for real-world quality control and security testing.

  
  

What It Means:

• Manufacturers can proactively address defects, reducing production costs and delays.

• Faster issue resolution leads to increased throughput and efficiency.

• Improved traceability simplifies compliance and corrective action processes.

• Centralised data approach improves decision-making, driving smarter, more optimised manufacturing.

• Heightened security ensures part integrity, especially in critical sectors like space and defence.

• Demonstrated real-world success sets the stage for broader industry adoption and future AI-driven automation.

Challenge

Traditional quality control in additive manufacturing is often reactive, relying on manual inspection and post-build analysis. This approach is time-consuming, costly, and prone to human error. Manufacturers require real-time insights to detect defects early and optimise production efficiency.

Solution

The integration of Addiguru's intelligent monitoring system with Authentise’s Manufacturing Execution System (MES) bridges the gap between process automation and AI-driven quality control.

Results

Early deployments have reduced material waste, improved production efficiency through real-time defect detection, and enhanced part-level traceability, with successful real-world implementation at i3DMFG validating the system in production.

in detail:

The Solution:

The integration of Addiguru's intelligent monitoring system with Authentise’s Manufacturing Execution System (MES) bridges the gap between process automation and AI-driven quality control. This collaboration enables:

• Real-Time Defect Detection: Addiguru’s AI-powered algorithms identify defects as they occur, minimising waste and reducing production time.

• Streamlined Decision Making and Part-Level Traceability: Review and react to defects. Fast track replacement parts and avoid wasted time post processing bad parts and fast track replacement parts. Link defects directly to parts for secondary Nonconformance review and CAPA (Corrective and Preventive Actions) processes. 

• Seamless Data Integration: Users gain access to a unified interface that consolidates production and quality data, allowing for data-driven decision-making.

• Enhanced Security & Surveillance: Addiguru’s system includes a camera-based monitoring solution, providing continuous oversight of the printing process. This ensures not only greater quality control but also heightened security, particularly for safety- and medically critical parts. In industries where digital infiltration and sabotage are concerns, such monitoring helps detect anomalies in real time, protecting the integrity of the manufacturing process.

The RESULTS:

Early implementations have demonstrated:

• A reduction in material waste due to proactive defect detection.

• Improved production efficiency, with real-time insights leading to faster issue resolution.

• Enhanced traceability through continuous monitoring and automated reporting.

• Successful deployment at i3DMFG, a partner company, where Addiguru’s system has been integrated for enhanced quality control and security. This marks a key milestone in real-world implementation.

What's Next...

FUTURE OPPORTUNITIES

Scaling AI-Driven Quality, Security, and Automation

The collaboration between Authentise and Addiguru paves the way for further advancements, including:

• Integration with CyManII, (The Cybersecurity Manufacturing Innovation Institute), to further enhance security and traceability in additive manufacturing.

• Expanded AI capabilities to refine defect classification and predictive maintenance.

• Deeper industry adoption by tailoring solutions to specific sectors such as defence and space industries.

• Integration with machine learning models to enhance process optimisation over time.

• Automated Workflow Adjustments: Authentise doesn’t currently provide an automated ‘If this, then that’ response to AddiGuru’s defect observations. At this stage, we offer manual review and intervention. Once the entire system proves to be reliable, automation would be the natural next step.

CONCLUSION

From Reactive Inspection to Proactive, Data-Driven Quality

By integrating Addiguru’s AI-driven monitoring with Authentise’s digital workflow solutions, manufacturers can move beyond traditional quality control and embrace a proactive, data-driven approach. This partnership not only enhances production efficiency but also sets a new standard for quality assurance in additive manufacturing.