Model-Based System Engineering Training

Overview: Trained inexperienced engineers, including those with non-automotive backgrounds, on using Model-Based System Engineering (MBSE) to derive system architecture, requirements, and component specifications from stakeholder needs.

Challenges: Preventing trainees from bypassing analysis to jump to familiar solutions, and adapting MBSE for diverse backgrounds.

Solution: Guided trainees through MBSE techniques, using a non-automotive system exercise to establish a clear framework and reinforce structured analysis.

Outcome: Successfully equipped the team to systematically develop system architecture and specifications, enhancing their MBSE proficiency.

 Overview: Developed a framework to guide engineering teams in selecting sensing technologies for ADAS, defining sensor specifications, vehicle placement, and failure modes based on driving scenarios.

Challenges: Limited team knowledge of sensing technologies, their trade-offs, and product lifecycle from inception to decommissioning.

Solution: Created training materials and frameworks for developing accurate digital twins for ADAS, enabling early concept validation. Defined methods for early failure mode identification and mitigation, integrating functional safety and cybersecurity in initial design phases.

Outcome: Delivered robust frameworks and training, ensuring accurate sensor specifications, optimized placements, and proactive safety/cybersecurity integration, minimizing late design changes.