3D-Master for a Digitized Manufacturing Platform
Enhancement of a digital platform for the manufacturing of prototype parts using various production technologies. The platform enables quotation generation within one minute and employs AI-based interpretation of engineering drawings considering geometric dimensioning and tolerancing (GD&T).
Result
In this Innosuisse project (Master3D), a cloud-based platform for the automated and transparent cost and price estimation of manufactured parts was developed. The solution integrates multiple manufacturing technologies, including milling, turning, polymer and metal additive manufacturing, as well as sheet metal processing, within a unified system. The platform is based on process-oriented cost models, such as Time-Driven Activity-Based Costing (TDABC) for additive manufacturing, which automatically derive manufacturing times and costs from CAD data (STEP exports). A particular focus was placed on the use of artificial intelligence to extract and map tolerance and quality information from technical drawings to 3D models. This made cost-relevant product information available for automated quotation and pricing processes.
The project also demonstrated the significant impact of customer-provided data quantity and quality on the accuracy of cost estimation, particularly in the field of additive manufacturing. Using the Formal Quality Level (FQL) concept, which evaluates the completeness and quality of the uploaded product data, different sources of uncertainty in cost estimation could be identified and quantified (expressed through a Key Performance Indicator (KPI), as shown in the figure). These uncertainties were subsequently incorporated into the pricing strategy through appropriate risk and confidence adjustments.
The project achieved fully automated quotation generation in less than one minute and showed good agreement with manually generated quotations in validation studies. The results provide a foundation for further research in digital manufacturing chains, Design for Manufacturing (DfM), and AI-supported document analysis.
Description
We enhance Bossard's Real Time Manufacturing Services by automatically creating quotes for special parts. The core is an AI-created 3D Master that unifies all available part information, enabling pricing and feasibility evaluation for many manufacturing technologies (such as milling and turning) incl. additive manufacturing.
Key data
Projectlead
Deputy Projectlead
Project team
Frank Huber, Sascha Hänzi, René Klopfer, Benjamin Meyer, Dr. Ahmed Abdulkadir, Lauro Singenberger, Silvan Lack, Erdal Ayfer, Lukas Tuggener, Dr. Briac Lanfant
Project partners
Bossard AG; Ergon Informatik AG
Project status
completed, 12/2022 - 05/2025
Institute/Centre
Institute of Product Development and Production Technologies (IPP); Centre for Artificial Intelligence (CAI)
Funding partner
Innosuisse Innovationsprojekt
Project budget
1'000'000 CHF
Publications
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A document is worth a structured record : principled inductive bias design for document recognition
2026 Meyer, Benjamin; Tuggener, Lukas; Hänzi, Sascha; Schmid, Daniel; Ayfer, Erdal; Grewe, Benjamin F.; Abdulkadir, Ahmed; Stadelmann, Thilo
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A unified cost estimation framework combining milling, turning, AM, and sheet metal processing
2026 Lack, Silvan; Lanfant, Briac; Hänzi, Sascha; Klopfer, René; Meyer, Benjamin; Abdulkadir, Ahmed; Stadelmann, Thilo; Schmid, Daniel
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Suitability of STEP file format with PMI for automated quotations
2026 Hänzi, Sascha; Thinagar, Sivaraman; Schmid, Daniel
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3D-master-based method for optimizing the cost calculation of PBF-LB/M manufactured parts
2025 Lanfant, Briac; Lack, Silvan; Meyer, Benjamin; Abdulkadir, Ahmed; Stadelmann, Thilo; Schmid, Daniel
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Design and release process for additive manufacturing parts
2024 Schmid, Daniel
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3D-master-based method for optimizing the cost calculation of PBF-LB/M manufactured parts
2024 Lanfant, Briac; Lack, Silvan; Meyer, Benjamin; Abdulkadir, Ahmed; Stadelmann, Thilo; Schmid, Daniel