Securing your workflows
Description:
In complex systems engineering environments, organizations rely on diverse tools, standards, and distributed teams to develop increasingly sophisticated systems. While vast amounts of engineering knowledge are generated—requirements, models, simulations, and verification artifacts—this knowledge often remains fragmented, inconsistently defined, and difficult to reuse. As a result, teams repeatedly recreate existing assets, leading to increased costs, longer development cycles, and reduced engineering efficiency.
This webinar explores how to enable systematic reuse of systems engineering assets by applying AI across heterogeneous tool ecosystems. It introduces a practical, incremental approach based on five key capabilities:
- Identifying reusable assets
- Qualifying the assets through quality and traceability criteria
- Classifying and discovering knowledge
- Adapting and integrating artifacts across tools
- Measuring reuse effectiveness through engineering metrics
Central to this approach is the use of modern AI techniques, LLMs, semantic technologies, and ontology-driven frameworks to harmonize meaning across tools and standards, enabling true interoperability and consistent reuse.
Rather than relying on large-scale transformation programs, the webinar will show how reuse can be implemented step by step by solving real engineering problems through targeted use cases. You’ll learn:
- How to reduce non-recurring engineering effort using modern AI technology
- How to universalize the quality and consistency assessment to the engineering items of your tool ecosystem
- How to reuse through interoperability
- How to build a scalable, knowledge-centric engineering environment that supports digital engineering reuse at enterprise scale, and with no effort
Date:
Thursday, May 28, 2026, 4:00 PM CEST (Madrid)/ 7:00 AM PDT (Los Angeles)/ 10:00 AM EDT (Detroit)/ 11 PM JST (Tokyo)
Registration: