6-month Internship
il y a 3 jours
About us:
Headquartered in France with offices in Singapore, Spare Parts 3D edits DigiPART™, a unique end-to-end software which enables to apply additive manufacturing to spare parts and reduce obsolescence, lead times, minimum order quantity, inventory levels in various sectors (Railway, Oil and Gas, Semiconductors).
About the Project:
With the progress of additive manufacturing (AM) techniques, major manufacturing industries are now transitioning parts of their production to AM processes. These technologies rely on a numerical chain, at the root of which lies CAD representations of parts to manufacture. While CAD models are now considered standard practice, manufacturers often possess large catalogues of legacy parts defined only as engineering drawings, with critical parts sometimes relying on such documents for production.
To support the shift of manufacturers from traditional to advanced manufacturing techniques, Spare Parts 3D built a 3D reconstruction system to create CAD models from multi-source engineering drawings, processing both raster (png, jpg, tif, pdf…) and vector files (namely DXF/DWG or vector PDF). A pipeline of processing modules combining traditional computer vision and deep learning extracts drawing features from drawings. The extracted information is processed through a custom, computational geometry-based reconstruction algorithm to build 3D models.
What you'll be working on:
Evaluating our solution to push its industrialisation forward is critical. To this end, we are creating a custom technical drawing dataset and designing a detailed evaluation pipeline. We aim to efficiently discover cases where the drawing-information-extraction pipeline and the reconstruction algorithm might fail and record the performances of every module in the entire system along consistent metrics, some still to be defined. Building upon the evaluation results, we wish to consolidate our modules (deep learning models, traditional computer vision algorithms, production code) and design more efficient solutions.
The envisioned internship work is as follows:
● Help define metrics to evaluate our information extraction and reconstruction modules.
● Run our entire pipeline over untested drawings and record the results in a detailed performance table.
● Identify, within our algorithms, steps and code snippets that bring the most significant error factors.
● Participate in incremental pipeline improvement, bettering models and adding traditional algorithmic methods to ensure robustness.
● Consolidate auto-annotation systems for drawing labellisation.
● Participate in manually annotating drawings and validating automatic annotations.
Work Environment
You'll work on a daily basis with the team, PhDs, PhD student, AI engineer. The role will be supervised by Spare Parts 3D's CPTO. Most of the team is based in Paris and meets on a weekly basis, but we accept remote applicants.
Who you are
- A generalist or mechanical engineer student in a French or European school or university, with good knowledge of Python,
- Capacity to communicate in English or French
- Engineering schematics reading is a strong plus
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