Analysing ODX Data

Transparency and security for ODX data from different sources

In everyday commercial vehicle development, ODX data often does not originate from in-house creation, but is sourced from a wide range of manufacturers and suppliers across different platforms, vehicle variants and generations. The same technical facts can be modelled in different ways. In order to correctly use, evaluate and further develop diagnostic functions, a deep understanding of the underlying ODX structure is required – especially in complex, long-lived commercial vehicle architectures.

DSA supports OEMs in the systematic analysis and classification of existing ODX data sets for commercial vehicles. The aim is to make the origin, structure and meaning of the diagnostic data traceable and to ensure its suitability for use in diagnostic and test environments throughout the vehicle life cycle. The analysis is carried out on a control unit basis as well as across the entire vehicle, regardless of whether the ODX data was created internally or supplied by external partners.

ODX structure and modelling analysis

Analysis of the structure and modelling of existing ODX data
Understanding different modelling approaches for the same diagnostic content across suppliers and vehicle variants
Testing of diagnostic services, data identifiers and error codes
Identification of inconsistencies, redundancies and deviations within complex ECU landscapes
Evaluation of usability in diagnostic and test systems for development, production and after-sales

PRODIS.OFT is used as an ODX-compliant front-loading tester for the analysis and understanding of ODX data in commercial vehicle projects. PRODIS.OFT enables structured navigation through ODX content and helps to make the origin, meaning and effects of individual diagnostic elements in the system context comprehensible across platforms and generations.

ODX analysis creates transparency about existing diagnostic data, reduces risks during integration and use, and forms a robust basis for stable, scalable diagnostic functions and the targeted further development of commercial vehicle diagnostic systems.