Meet Grey

Grey-1 is our next-gen AI brain for additive manufacturing. Already equipped with advanced error detection, parameter prediction and optimisation capabilities, Grey continues to learn with every print within our global network of 3D printers.

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Powered by Matta's global data engine

Grey-1 learns via deep analysis of industrial data, obtained from our global network of 3D printers.

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Pop the hood

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Recycled PLA • Consumer product • Home decor item
Ultrafuse 17-4 PH • Engineering part • Helical gear
ABS-X • Product prototype • Cable tidy solution

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Moving on

Detects errors in real time

Grey-1 can autonomously monitor additive manufacturing process and find errors in real time.
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Rapidly identify printing errors

Trained on countless hours of extrusion printing data, Grey-1 is able to find printing issues fast with remarkable accuracy.

Intelligent and robust, Grey-1 exhibits excellent performance across a wide number of geometries, materials, printers, toolpaths and even extrusion methods. We hope to train Grey-1 further to be able to find errors across a plethora of manufacturing processes, and to find new applications for its outputs.
Bed detachment
Poor first layer
Layer offset
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error
User notified
Status: Printing

Part: XYZCube.gcode (432kB)
Layer: 41

Printing time: 32 minutes
Estimated time remaining: 10 minutes

Errors detected: 4
Print quality estimate: 60%

Recommended adjustments:

• Reduce printhead acceleration
• Check XY belt tensions
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Drag to pan through print

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Continue

Generates and analyses digital twin parts

Grey-1 creates digital models of printed parts using G-code, mapping errors to localised regions.
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Supercharged quality control

Without expensive or time-consuming scanning methods, manual QC is limited to outer faces of parts. However, Grey-1 sees every inch of parts during the printing process, inside and out, making it a powerful tool for qualification.

Using a variety of data streams, Grey-1 maps identified printing errors to their specific locations on parts. Using G-code, Grey-1 then generates a digital twin of the part, and projects quality measurements onto each extruded line, ready for inspection.

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Slide to compare a real part with Grey-1's predictive quality digital twin
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What else can Grey do?

Corrects errors on the fly

Grey-1 learns not only to find errors, but to identify their causes. Combined with closed-loop control algorithms, Grey-1 can correct sub-optimal parameters on the fly, ensuring top quality prints, first time.
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Manufacturing autopilot with parameter correction

Grey-1 can monitor printing parameters, such as flow rate or z-offset, and predict their deviation from optimal. When used in parallel with closed-loop control algorithms, Grey-1 becomes a manufacturing autopilot, continuously controlling parameters throughout the printing process to minimise the probability of errors and maximise quality.

In the video examples in this section, parameter-dependant printing errors were artificially generated while printing. Grey-1 can be seen to quickly identify the problem and its cause, then make the required adjustment to the parameter, returning print characteristics to nominal.
Flow error
Speed error
Z-offset error
Hotend error

Learns to print new materials

Grey-1 has learned enough about the fundamental physics of extrusion processes, that it can work out how to print new unseen materials.
Grey enables next-level batch-to-batch material qualification by discovering optimum processing parameters within seconds of printing.
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Material profile discovery

Grey-1 was only trained on PLA, but is programmed to learn in a way that makes its knowledge transferable between materials. Watch Grey-1 find the optimum processing parameters for materials it has never seen before in this section.

In these examples, parameters are generated randomly at the beginning of the print. Grey-1 then quickly analyses the visual data, identifying and executing adjustments to increase quality until optimum print characteristics are obtained.
ABS-X
CF Nylon
PVA HT+
TPU

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