AUTOMOTIVE INDUSTRY
Validation of the TSN/CAN Platform
ALTEN Polska supported a leading semiconductor solutions provider in delivering the complete validation process for a new industrial platform compatible with TSN standards and the CAN bus. Our team delivered an end‑to‑end testing solution that enabled effective detection and elimination of product weaknesses, significantly improving its quality and reliability.
ALTEN Polska’s expertise included building a flexible testing framework from scratch, implementing test scenarios, and fully integrating the CI/CD process. Thanks to advanced knowledge in Automotive, TSN networks, Python, and automation tools, the project was executed quickly and in line with the highest industry standards. A key element of the work was the implementation of AI‑based solutions that accelerated test result analysis and automatic anomaly detection.
Challenge
Creating a scalable and flexible testing framework for a platform supporting TSN standards as well as various hardware configurations and communication protocols.
Solution
Development of a modular Python‑based testing framework, implementation of requirement‑based test cases, integration of AI‑assisted test analysis, and deployment of a stable CI/CD process.
Benefits
- Full automation of the validation process
- A scalable framework capable of testing multiple hardware configurations
- Reduced error detection time thanks to AI‑supported analysis
- Improved reliability and quality of the final product
- Reduced technical debt through the use of modern Python libraries
Importance of project challenges and their impact on end users
The project focused on an advanced networking platform used in industrial and Automotive applications, where reliability and predictability of data transmission are essential. TSN standards such as IEEE 802.1AS, 802.1Qbv, 802.1Qbu, and 802.1CB require rigorous validation to ensure deterministic communication in real‑time systems. The challenges involved both the complexity of the testing environment and the need to prepare tests covering various interface speeds and transmission media. Eliminating potential issues at this stage had a direct impact on the safety and comfort of end users—especially in Automotive, where even minor errors may affect the operation of safety‑critical systems.
Tools and solutions implemented in the project
The ALTEN Polska team developed a Python‑ and pytest‑based testing framework supported by an extended networking stack, enabling the execution of complex automated tests. Engineers created a modular architecture capable of handling various hardware configurations and transmission standards. AI‑driven algorithms were implemented to perform automatic test result analysis, faster detection of abnormal behavior, and anomaly reporting. The CI/CD process was optimized for repeatability, stability, and future scalability.
Key benefits for the client and end users
LINCOLN’s client plans to apply these advanced statistical techniques to ensure accurate detection of anomalies and losses. Using real-time monitoring and operational measures, they will be able to anticipate breakdowns (for example, blade breakage, rotor and generator bearing degradation), reducing the frequency and cost of interventions, minimizing energy losses and enabling proactive maintenance actions.
In this way, LINCOLN’s expertise in data analytics will contribute to improving overall productivity, boostingefficiency and reducing downtime.
