Peer Review of ADAS System Engineering for Trucks
Overview: Conducted a comprehensive peer review of system engineering work products for truck ADAS features, focusing on safety and reliability.
Challenges: Complex failure modes in control/user interfaces, inconsistent testing scenarios, and gaps in FMEAs.
Solution: Analyzed work products, evaluated failure modes, and reviewed testing procedures to identify improvement areas.
Outcome: Proposed enhanced system engineering processes, closed FMEA gaps, and improved testing methodologies by 20%.
Reverse-Engineering Vehicle Legacy Features
Overview: Reverse-engineered vehicle-level legacy features with limited documentation to rebuild system architecture and ensure functionality.
Challenges: Sparse documentation, unidentified components, and complex feature interactions.
Solution: Analyzed existing specifications, identified key feature characteristics and component interfaces, and developed system architecture using MBSE techniques.
Outcome: Produced detailed feature behavior analysis, resolved documentation inconsistencies, and delivered comprehensive system models.
Driver Monitoring System Design
Overview: Designed a Driver Monitoring System using Model-Based System Engineering (MBSE) within an Agile framework to enhance driver safety and meet regulatory standards.
Challenges: Evolving regulatory requirements, complex system integration, and defining precise performance metrics.
Solution: Reviewed legal standards, selected suitable technologies, developed system requirements and architecture, and established KPIs with robust testing methods.
Outcome: Delivered comprehensive system requirements, completed Functional Safety analysis, and conducted Threat Assessment and Risk Analysis, ensuring full compliance.
E/E Architecture Development Using MBSE
Overview: Developed a new Electrical/Electronic (E/E) architecture using Model-Based System Engineering (MBSE) to ensure robust system integration and performance.
Challenges: Complex system requirements, diverse component specifications, and alignment across feature owners.
Solution: Reviewed existing requirements and component documentation, aligned with feature and component owners on expected attributes, and built logical and physical system architecture models in PreeVision using MBSE techniques.
Outcome: Delivered comprehensive E/E architecture models, ensuring alignment and scalability for future integrations.