Quality Assurance / Sustainability in the Automotive Industry

Your challenges and our solutions

Automated 3D Digitizing and Inspection of Service Parts

High manual effort for inspection findings

Process times are reduced with automated detection and analysis of defects.

Our Solution

  • Automated recording of actual condition of service parts
  • Match actual geometry with CAD model
  • Automatically extract differential volumes for post-processing

 

Your Benefits

  • Simple inspection and repair of defects through automated recording of findings
  • Shorten inspection times through automated detection and analysis
  • Increase quality through consistent defect analysis and repair

Automated Object Recognition for Returns Management

Old parts not recognizable

Even without identification markers, old parts are recognized reliably and quickly. Intelligent data management and the latest training strategies in object recognition reduce the effort required.

Our Solution

  • Recognize used parts without markers based on images, despite different states of use and degrees of soiling
  • Automated provision of information for documentation
  • 4-eyes principle through assistance systems

Your Benefits

  • If identification options such as barcodes are no longer available or readable for used parts, the manual identification effort can be reduced. 
  • Profitability of the aftermarket is increased.
  • Spectrum of objects can be extended flexibly and independently.

Diagnosis of Products by Optical Surface Inspection

Error-prone manual quality inspections

New AI technology with minimal integration effort can be used for quality inspection of new and used parts.

Our Solution

  • Non-contact image-based quality assurance with state-of-the-art AI algorithms
  • Spectrum of defects to be detected can be flexibly and independently extended.
  • Holistic approach to problems through requirement-specific hardware and algorithm development

Your Benefits

  • Commercially available cameras can be used for defect inspection.
  • Digital positive documentation as proof of quality
  • Digital documentation for downstream process optimization

Energy-efficient Production

High energy costs in production

Digital transformation opens up new opportunities in energy management to optimize energy and resource efficiency for industrial production.

Our Solution

  • Create energy concepts
  • Collect and evaluate data
  • Energy management to try out

 

Your Benefits

  • Find and exploit savings potential from supply to production
  • Optimized generation of hydraulic power, among other things
  • Interaction with real control technology possible

Decision Support at Vehicles’ End of Life

Recycling and reuse not sustainable

Decision support in choosing a suitable recycling strategy reduces the CO2 footprint at the end of a vehicle's life.

Our Solution

  • Identify feedback cycles between vehicle use and recycling up to development
  • Capture and analyze requirements for digital twins from a product perspective and design them in a user-centric way
  • Support decision making of suitable cycle strategies and develop appropriate R-strategies

Your Benefits

  • Consider end-of-life reuse and recycling options of vehicles individually
  • Extend service life with information from digital twins
  • Resource efficiency is increased and regulations (e.g. secondary materials, recycling quotas) are easier to comply with.

Design Levers for Sustainable Vehicles

Increasing demand for sustainable components in vehicles

Methodical analyses identify design dependencies and optimize the development of sustainable vehicles at an early stage.

Our Solution

  • Analyze product system boundaries and derive tools and methods for use cases from it
  • Model system architectures (e.g. in SysML) for quantification of sustainability indicators
  • Develop integration options and design levers for existing product system development based on 9R strategies

Your Benefits

  • More sustainable product systems in the long term to increase competitiveness
  • Increase circularity and thus resilience in unstable supply chains
  • Models can be reused for future product generations.

Intelligent Wear, Equipment and Process Monitoring

Machine failures are unpredictable

Machine tool condition monitoring makes machine failures predictable. Maintenance and repairs can be planned in time over the entire life cycle.

Our Solution

  • Acquire data internally in the control system and via external sensors
  • Monitoring with real-time data analysis
  • Develop application-related digital twins

 

Your Benefits

  • Transparency and security of data is ensured by documenting the machine history over the entire life cycle.
  • Detect even the smallest damage with sensor support and predict critical machine conditions
  • Design maintenance measures more efficiently

Sustainable Vehicles through Digital Twins

Lack of transparency of ecological indicators

Digital twins enable early forecasting that promotes sustainable product development.

Our Solution

  • Develop user-centric Digital Twins
  • Link ecological indicators and design parameters
  • Derive recommendations for action and optimization through

 

Your Benefits

  • Monitoring and early forecasting of sustainability indicators from product development to product use in the digital twin
  • Early optimization of sustainability in vehicles
  • Preparation for future sustainability requirements

Sustainability-based Feedback to Design

Fleet-based data to optimize design decisions

Developing an individual target image for feedback-to-design enables CO2 savings, among other things.

Our Solution

  • Identify feedback cycles between use and recycling of vehicles up to their development
  • Capture and analyze requirements from a product perspective
  • Design data and architecture for digital twins in a user-centric way

 

Your Benefits

  • Better information in development through evaluation of fleet-based data
  • Save CO2
  • Comply with regulations, such as secondary materials or recycling quotas