Quality Assurance / Sustainability in the Automotive Industry

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

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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.

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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

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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

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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

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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