Software & Data Management (Lifecycle)

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Increasing sensorization enables the end-to-end digitalization of the product development process as well as the digitalization of the product itself (digital twin). This also includes the monitoring of products along the entire product development process and over the product life cycle in real time. By means of machine learning applied across all component-specific lifecycle data records, it is possible to obtain effective relationships between, for example, use and load or load and damage progression, which can be used in the next product generation for component optimization and successive improvement of the design tools used along the product development process.


  • Continuous data acquisition along the life cycle
  • Data management concepts along the life cycle, along the supply chain and across value chains
  • AI-based analyses of real data to derive cause-effect relationships.