Automate quality

Accurate data collection for in-process inspection and NCR management

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Trusted by the leading players

Spector helps technicians create accurate quality records in AR and validate correctness with AI.

In aerospace, quality is non-negotiable. When nonconformance is identified, the burden of defect reporting, engineering disposition, repair, and reinspection causes delay and creates excessive inventory.

We developed Spector, the platform that allows to capture accurate location of the defect on a part in Augmented Reality together with the picture and other characteristics such as type, size, and part number. This helps to reduce cycle time due to higher accuracy and clarity of inspection data, real-time tracking status defect, and faster workflow facilitated by automatic contextual access to repair limits and instructions. Machine Learning helps to detect the defects and validate correctness of the final assembly.

BENEFITS

Reduced cycle time

Higher accuracy of the inspection data with the defect location captured unambiguously on the 3D model of the inspected part and pictures and videos enabling engineering disposition without requesting additional data
Higher transparency of the inspection and repair status supported to the real-time picture of all unresolved defects shared between the shop floor and engineering
Faster inspection and repair workflows due to the availability of the repair limits, instructions, and acceptance criteria contextual on the markers

Increased quality

Allowing technician to validate the decision with the help of Machine Learning algorithm reduces the risk of overprocessing or vice versa — missing the defect and ensures higher consistency of the quality control process

PROCESS

Inspect

Flag the issue with the marker in Augmented Reality and document findings by attaching digital notes and pictures

Resolve

Receive location-specific repair instruction on the shop floor, analyze digital records with engineering in complex cases

Automate

Detect and classify defects automatically with Machine Learning algorithms

FEATURES

AR headset brings new powerful sensors on the shop floor

Spatial awareness, one of the core capabilities of the AR headset, helps connecting digital with physical distributing technical information to the point of use

Marker coordinates in space are generated automatically. This provides the repair crew not only accurate defect location but also measurements of the size, area, and distance to other objects.

Pictures, videos, notes, and historical maintenance data are linked to the marker enabling stress-free engineering disposition. Availability of consistent historical data supports more sound trend analysis.

Depending on its location marker provides access to the relevant repair instructions and historical data. It becomes a spatial quality record storing pictures, notes, and sensor readings over time.

The algorithm helps to detect and classify surface defects while upon completing the repair the correctness is again confirmed via the automated system.

Instant Measurements

Rich Media Layer

Contextual Instructions

Automated Quality Assurance

IT INTEGRATION

Spector has the integration-ready REST API allowing to connect with existing enterprise data sources, ERP/PLM/MES. The system could be implemented on-premises or in the cloud of choice. Individual user profiles align with the roles and responsibilities of the department.

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