Success story
Partnered with a leading passenger car OEM to re-imagine their diagnostic data authoring and
management approach
In typical OEM set-ups, diagnostics requirement data is managed in proprietary data formats, and is used across OEM departments, in addition to Tier X suppliers & tool vendors.
Ideally, a development process needs to ensure data transparency, uniformity, and re-use. However, the lack of
a standardized, integrated & an automated diagnostic approach results in development silos and
disparate tooling/data systems.
The Engineering diagnostics toolchain from KPIT provides the answer. The toolchain has been at the core of addressing these challenges & transforming the diagnostic development landscape at leading automotive/industrial equipment OEM.
Database Designer
ECU Editor
Authoring Suite
Engineering Tester
ECU Validator
It caters to all diagnostic engineering use-cases across the OEM vehicle development process, and enables system, component, and function engineers to seamlessly execute activities, including
Diagnostic requirements development
ECU diagnostic data authoring
Developing test sequences for ECU validation
Executing ECU sequence and conformance tests
A cloud-based enterprise integration platform joins all the engineering functions together, connecting the dots from requirements sign-off through to automated compliance gateways; automating data flow and eliminating legacy processes (such as manual file handling).
Integrated dashboards provide up-to-the-minute insight into development maturity and place our customers
firmly in control of their diagnostic artifact delivery.
An integrated & an automated approach for diagnostic data design, data creation /management and ECU validation
Enables left-shifting of testing & verification
Drives data uniformity, transparency, and re-use across the ecosystem
Uniquely positioned to support OEM, as they face diagnostic complexities arising from their Electrification and Autonomous programs
Partnered with a leading passenger car OEM to re-imagine their diagnostic data authoring and
management approach
