Participants in continuing education, further training to become a quality engineer learn about various quality methods across the entire product life cycle, are familiar with the basic statistical principles of quality assurance and can use these to correctly interpret and control measurement and CAQ systems. They also have a comprehensive understanding of quality, from recognizing relevant requirements to optimizing testing processes.

The target group for continuing education, further training to become a quality engineer are designers, quality specialists, process planners and quality managers who want to take on demanding tasks in quality assurance, as well as for coaches for preventive methods for product development process quality assurance.

The continuing education, further training to become a Quality Engineer is extremely comprehensive in terms of content and consists of a total of 13 modules, including the exam simulation. The following modules are also taught:

• Fundamentals of quality work
• Advance quality planning and inspection planning
• Test concepts and test methods
• Quality assurance with store floor management
• Measurement system analysis
• Design for Six Sigma
• Statistical process control
• Random sampling according to AQL
• Technical risk analysis
• Product development process requirements
• Statistical evaluation methods
• Statistical experimental design

The Quality Engineer course covers a period of around six months with a total of 23 attendance days.

Within two hours, participants in the Quality Engineer certificate examination are tested in writing in the following areas:

• Design for Six Sigma
• Product development process
• Technical risk analysis
• Statistical experimental design

After completing the Quality Engineer course, participants will be able to understand quality assurance in the context of the company and select and plan targeted quality assurance measures. They will be able to promote the quality culture through visualization and transparency, prepare and evaluate data graphically and computationally effectively and be familiar with statistical methods such as sampling and SPC.