Spare Parts 3D (SP3D), the French software Startup, has launched a beta programme for Théia, a new AI-Powered 2D-to-3D Model Digitization Tool. As global geopolitical and economic factors put pressure on supply chains, more businesses are looking to digitise their inventories, allowing spare parts to be 3D printed locally and on-demand. The digitization process, however, can be time-consuming and expensive.
SP3D’s new offering, which integrates with the company’s AI-driven DigiPart software, uses deep learning technology to convert existing 2D drawings of spare parts into 3D printable models, reducing conversion times from days to minutes.
Development of the Théia
SP3D’s new offering, which integrates with the company’s AI-driven DigiPart software, uses deep learning technology to convert existing 2D drawings of spare parts into 3D printable models, reducing conversion times from days to minutes.
The Théia 2D-to-3D printing software was announced in 2022 as part of a joint R&D project with the French Defence Innovation Agency (DIA) and the École Normale Supérieure Paris-Saclay’s University for Research in Automated Production (LURPA).
“Théia addresses two major challenges: on one hand, reading, understanding and interpreting the information present on the drawing, and on the other, obtaining a 3D shape from its representation on 2D plans, while respecting the geometric and dimensional specifications of the original object.”
– Professor Nabil Anwer, Professor at Paris-Saclay University and Deputy Director of LURPA
SP3D claims that its new tool lowers the cost of digitization. This will allow more companies to use additive manufacturing to produce spare parts, lowering physical inventory costs. Théia claims that by digitising inventory, companies can save $34 billion per year.
SP3D’s DigiPart software
SP3D’s DigiPart software uses artificial intelligence to identify, digitise, and 3D print spare parts. The offering is aimed at businesses in a variety of industries looking to build cost-effective, end-to-end digital spare parts inventories.
This software allows users to identify and map their 3D printable parts. The platform then recommends which materials and 3D printing processes are best for each part, connecting the user with a 3D printing service provider for manufacturing.
DigiPart has received interest from a number of multinational clients, including Honeywell, a manufacturing conglomerate, and DNV, an assurance and risk management company. Furthermore, it was announced in 2020 that Brazilian petrochemical company Braskem had implemented the software to improve supply chain efficiency and reduce overall spare part spending.
2D-to-3D Model Digitization Tool
Access to 3D printable models of industrial equipment and parts is a major barrier to the widespread adoption of additive manufacturing. The majority of these parts are only available as 2D technical drawings. Traditionally, these drawings must be manually processed by an engineer to produce a 3D model, a laborious process that can take up to a day per part.
SP3D’s new Théia software automates this process by combining deep learning, computer vision, and existing semantic optical character recognition (OCR) capabilities. According to Anwer, this combination identifies and interprets various semantic layers of a 2D technical drawing to optimise 3D reconstruction.
This offering is said to allow for significant storage cost savings and the immediate availability of locally 3D printed spare parts. As a result, businesses can reshore their supply chains, enabling faster and more secure access to critical components.
Paul Guillaumot, founder and CEO of Spare Parts 3D, describes Théia as a “world first” that will enable large-scale digitization of supply chains in industries with high spare part demand, such as energy, defence, petrochemicals, railways, shipping, and mining. The new software also contributes to France’s Ministry of Defence’s innovation policy by ensuring the operational readiness of its military equipment.
Environmental benefits have also been highlighted as a key selling point for this new digitization tool. According to SP3D, combining digital catalogues with additive manufacturing can eliminate stock obsolescence and improve part repairability. This can extend the life of machines while reducing waste.
Furthermore, by bringing production closer to the point of need, Théia can help reduce transportation-related CO2 emissions. Indeed, at COP 28, UN officials identified increased digitization of supply chains as critical to industrial decarbonisation efforts.
SP3D has issued a call for industrial beta testers to participate in a Théia trial, with the goal of generalising 3D reconstruction from drawings and parts of any complexity. SP3D also hopes to speed up the creation of parametric files, allowing the software to automatically modify models based on the manufacturing processes selected.
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