Learn specifics about projects and processes in automotive engineering, leveraging AI to streamline quality assessments and review critical work products.
This course brings the essential understanding of automotive quality management, as an essential prerequisite for safe and secure releases, as well as ways to leverage AI in quality assessment and review. The key concept of the training is to bring an understanding of why quality, process, and project management are basics for producing safe and secure vehicles. By the end of the course, you will learn how to grow a quality culture and ensure organizational strength by using a specific quality measurement framework. Furthermore, the course will bring the importance of processes and procedures, the connection between safety and quality management, and the project management process through automotive recommendations and standards. We will uncover how AI tools can be integrated to simulate real-world assessment exercises, automatically read and analyze complex specifications, and verify the consistency of vital work products. At the end of the course, focus will be given to assessment procedures in order to ensure a deep understanding of how assessments are held in the automotive industry as requested by the majority of OEMs.
Course Topics:
- Quality management, organizational strength triangle, quality dimensions and disciplines, main principles of Quality Management System (ISO 9001), key characteristics, PDCA (Plan-Do-Check-Act) cycle.
- Key Performance Indicators (KPIs) and Key Activity Indicators (KAIs).
- Automotive SPICE: The basic concept of measurement frameworks with specific insights on ASPICE (ISO 15504).
- Project management: The management process through the ASPICE framework including best practices and work products mandatory to fulfill ASPICE Level 1 and BPs.
- Quality Assurance, Configuration Management, Problem Resolution, Change Request Management. Utilizing AI to review and validate change requests and problem resolution logs.
- Engineering processes Development: Traceability and basic practices of system and software requirements, as well as system design and software architecture together with unit construction processes. Using AI to read specifications, analyze requirements for clarity, and assist in simulating development exercises.
- Engineering processes Testing: Traceability and basic practices of system, software, and unit testing on all levels. Applying AI to automatically check traceability matrices and verify bidirectional traceability to ensure ASPICE compliance.
Requirements
Software: Chrome browser, and access to modern AI tools (e.g., ChatGPT, Claude) for document analysis and simulation.
Hardware: Computer with an Internet connection, working speakers, and microphone.
Prior knowledge: Students should have a basic understanding of projects from their previous engineering or technical experience or previous studies. Students shall have basic knowledge of system and safety engineering.
