As a leading global provider of systems and components for seats, overheads, doors, cockpits and electronics, the Automotive Experience team is continuously looking for advanced technology solutions that can reduce product weight, provide a step-change cost reduction, and/or improve our environmental sustainability. We especially encourage technology ideas within one of these topic areas:

Materials Technology
  • Innovations that improve foam damping performance while reducing weight and/or thickness
  • Bio-composites or natural fibers ready for industrial scale-up and high volume production
  • Trim solutions to replace conventional fabric, vinyl and leather materials
  • Functional integration of non-structural composites to improve acoustics, stiffness and VOC reduction
  • Advanced high strength steels and other lightweight metal technologies
  • Alternatives to steel, such as structural composites, for making lightweight interior parts

“Smart” Surfaces/Human Interaction

  • Mechatronic solutions based on “smart” materials and technologies with multi-functional behavior
  • Lighting technology for accent, ambient, instrumentation, and display graphics
  • Sensor and actuator technology for electronification of interior features
  • Innovations that enhance human performance, reduce errors, and increase safety and user satisfaction
  • Surface/skin technologies that enhance look & feel, gloss level, haptics, aesthetics and acoustics
  • Improvements to existing metallic, technical and woodgrain decorative technologies, and special effects
  • Safety technology, such as crash energy management in hybrid/electric vehicles

Manufacturing/Tooling/Assembly
  • Tooling technology for injection molding that reduces manufacturing cycle time
  • Advanced welding/joining technology for unconventional or dissimilar materials
  • Advanced precision forming or novel technologies to downsize mechanical components, such as recliners
  • Assembly automation that reduces cost, complexity, and/or cycle time
  • Software tools that improve predictive analysis and design optimization

Submission Form