The success of any vehicle program lies above all in its beginning and whether the right choices were made when selecting a concept to proceed with. The increasing number of models and variants combined with architecture options leads to an overwhelming amount of possibilities to pick from. Thus, having the assessment as accurate as possible is becoming critical in order to predict the consequences of such choices. Further, concept engineers have a very short time to perform evaluations, very limited data so early in the development and many conflicting requirements to fulfill. Finding optimal designs at concept stage requires synchronized performance assessment across multiple disciplines. And yet architects and domain experts often work in isolation/silos resulting in little sharing and reuse of knowledge, achieving only suboptimal designs.
The 3DEXPERIENCE platform provides an environment that enables engineers to manage the complexity of early vehicle design choices. The collaborative environment brings together all processes, expertise and data gained from previous programs, or newly acquired through smart methods.
The Model-Based Systems Engineering approach provides structure in the development process, traceability and early insight into system interdependencies. Initial customer requirements are managed and propagated as specifications for each phase of development, from concept to detailed designs. Common data models between design and simulation and integration between different domains and scales (0D-3D) enable easier setup for holistic multidisciplinary performance evaluation. The tools to create and manage accurate predictive models facilitate carryover and reuse of gained expertise from older programs and existing design workflows. Usage of adaptive DoE, optimization technologies and machine learning helps to resolve conflicts between performance targets and discover optimal designs. Interactive design explorers, reusable workflows for non-expert users enabled by fast running simulations help designers understand the impact of design changes earlier. Web-based interactive dashboards and ranking algorithms for trade-off analysis support collective decision making.
The Performance Driven Architecture Industry Process enables companies to deploy multi-disciplinary trade-offs for conceptual, system and vehicle architecture to optimize the overall vehicle performance and quality and to identify risks and issues earlier, thus establishing a continuous process of product improvement.
