Next Level Digital Twin: Linking CAD-Data, Meta Data and AutomotiveWorkshop Media to Create a New Product Understanding
A Project between Porsche and Spread
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EDITOR: ALINA BIERMANN
A car consists of about 30,000 parts . When repairing a specific car part, workshop technicians use repair manuals: step-by-step guides on how to take out parts. To create these manuals, the workshop media editors need to understand the dependencies, e.g. how and where parts are connected to each other and need to identify special technical details, e.g. safety-critical parts, torque, time value. Obtaining such information previously required intensive and time-consuming searches in multiple sources, such as Excel lists, databases, PDFs, and required very experienced editors who are product data experts. With the electrification of vehicles and the accompanying change in vehicle architecture, new specific product knowledge must be built up for the editors, which must be communicated simply and intuitively in the workshops. Porsche has thus partnered up with the Berlin-based company SPREAD.
Porsche Aftersales defined a new workshop media strategy 2025+. The vision of the workshop media strategy is to develop a workshop digital twin . A one-to-one digital twin of a vehicle to link CAD-Data , Meta-Data and workshop media.
The strategy’s fields of action were defined as follows:
- Efficient Editing — Data-driven media creation [automated and inter-linked]
- On-demand Repair Route — Dynamic repair sequence [optimized for repair and work equipment]
- Intuitive Media — Situational repair assistance [adaptive and intelligent]
SPREAD was quickly identified as a potential partner because of its focus on developing precisely such a visionary solution: the creation of a product intelligence platform. With such a platform and its 3D analytical capabilities, SPREAD enables a comprehensive engineering understanding down to the smallest screw, while at the same time creating the basis for an intelligent digital twin, which can be easily enriched, with its product information model.
The Project
Within the context of Startup Autobahn, the use case “Intelligent Analysis of Neighboring Parts” was selected. It forms the basis for the automized enrichment of product data and the intelligent identification of part dependencies in 3D.
It consists of three capabilities and features:
- Neighboring Parts Analysis — Identification of directly (1st degree neighbors) and indirectly (2nd and 3rd degree neighbors) connected parts, for dependency analysis. Important to determine an order for demount sequences.
- Classification — Automated grouping of parts based on reference geometries and defined norm groups. In the first step, just for fasteners.
- Filtering of Neighboring Parts — Intelligent filtering based on classes (e.g. fastener butterfly valve, screw butterfly valve, nut butterfly valve), but also based on context-related CAD analysis, by integrating the classification in the neighborhood analysis.
As a first step, the design prototypes and the classification logic were defined. Using their 3D analysis capabilities, SPREAD was able to quickly and easily identify all potential fasteners based on their geometry and provide them as a proposal to the Porsche colleagues. With this knowledge, Porsche was then able to coordinate the definition of the classification logic with the group standardization logic and thus define standardization-compliant fastener classes.
Outcome
SPREAD’s technology has made it possible to significantly increase the digitalized product knowledge, by automatization of parts classification, increasing the depth of information and intelligent understanding of dependencies between each and every part. It enables intuitive navigation, analysis, and visualization of part neighborhoods in seconds to easily track dependencies with minimal manual effort.
The solution facilitates rapid product and part understanding, resulting in a 50% reduction of search and validation time. It represents the preliminary stage (first step) of the automated calculation of disassembly sequences. With the classification and enrichment of additional properties, it reveals a new level of transparency.
Future Outlook
Regarding the next steps, there is already a preliminary study underway to deepen the knowledge of the Startup Autobahn project and validate how the SPREAD solution can be further integrated into the Porsche infrastructure. In addition, extensions, and next steps on the way to the new digital, integrated and automated repair journey are being defined together with SPREAD.
Acknowledgements
We would like to express our sincere thanks to Joachim Kaiser (Porsche, VAT2), Marina Jilg (Porsche, VAT2), Frank Della Ducata (Porsche, VAT2), Antoon Willem Arie Versteeg (Porsche, FO), Michael Tonigold (Porsche, VAT2), Jonas Wutgen (Porsche, VAT1), Michael Kranz (Porsche, VAT2), Lena-Luisa Bartels (Porsche, VAT2) and Daniel Halbig (Spread).
About STARTUP AUTOBAHN
STARTUP AUTOBAHN powered by Plug and Play is an innovation platform moderating an in-depth and curated collaboration between core partners from industry and young tech companies. The program is stage agnostic and designed to accelerate startups by connecting them to the right business units of our Corporate Partners in order to lay the groundwork of a successful cooperation and eventually outstanding pilot projects, implementations or investments.
Plug and Play Tech Center, Mercedes-Benz AG, ARENA2036, University of Stuttgart, ZF, DXC Technology, Porsche, BASF, Webasto, Motherson, DPDHL, Bosch, Schaeffler, STMicroelectronics, Murata, AGC, Hyundai, Linde, BP, Wieland, Faurecia, Eberspächer, ADAC, Sekisui, Plastic Omnium, Zenzic, Maxion, Novelis, ITT, Grupo Antolin, Huf Group, CEAT
Contact for this project
Alina Biermann
Ventures Associate,
STARTUP AUTOBAHN powered by Plug and Play
alina@pnptc.com
Anja Mertens
Digitization & Innovation,
Porsche AG
anja.mertens1@porsche.de
Andy Grau
Innovation Manager
Porsche AG
andy.grau@porsche.de
Christoph Acker
Innovation Manager
Porsche AG
christoph.acker@porsche.de
