Automotive

Automotive

Automotive
Automotive

From engineering to after sales

The automotive industry is a classic example of industrialization. Automotive products also come in an extremely wide range of variations and require custom manufacturing: With so many complex configuration options, no vehicle is exactly like another.

Good information management takes this variety into account. Like production, information processes are also industrialized and range from development to product communication, workshops and diagnostics to the vehicles themselves (vehicle communications with OTX and ODX). In the opposite direction, feedback processes help companies benefit from comments and experiences worldwide, regardless of language or market.

Digital continuity

Information is recorded as soon as it is created, then stored and linked semantically.

Engineering changes are thus automatically incorporated into all possible views and publications as part of a continuous process: Changes to development parts lists are automatically reflected in replacement parts lists, diagnostic systems and user information.

» GRIPS: Information products with high value for the customer

Personalization

Customers want vehicles that are precisely configured in line with their expectations.

Accordingly, they expect personalized information products that they can make quick use of according to situational requirements.

In this way, you can create a positive customer experience.

» PRISMA for after sales

Intelligent linking for versatile use

Intelligent linking is already contained within the data model and therefore does not need to be subsequently manually created.

It allows the data to be used for any number of multi-channel publications: As PDFs for printed operating manuals and workshop literature, standard documentation for regulatory compliance or on interactive portals with semantic queries.

» Automated multi-channel production: Information in real time

Quicker diagnostics

Thanks to the semantic linking, the troubleshooting process is not bound by rigid decision trees: The most efficient way to achieve a goal is determined using probabilities, labor values and other parameters, as well as input from the internal vehicle diagnostics (ODX).

By evaluating the results of previous troubleshooting procedures, diagnostic processes can be continuously optimized.

» PRISMA for after sales: Artificial intelligence for products