Simulation Data Management:
What Do Manufacturers Want?

Ora Research Letter on Digital Prototyping, Simulation & Analysis April 17, 2009

By Bruce Jenkins, CEO

Across manufacturing industry, companies are working to make their use of digital simulation and analysis more efficient, effective and productive. At many, such as auto makers and off-highway equipment companies, the challenges center on making CAE usage more pervasive throughout product development, and advancing its use upstream to have earlier, better leveraged impact on product development. In other industries where CAE is already used early and pervasively, notably aerospace/defense and aircraft engines, the focus is on better integrating analysis tools of varying fidelities (i.e., those used in different stages of product development) and different disciplines, and on automating the work processes that employ them.

At manufacturers large and small, discipline leads and methods experts tell us that insufficient capabilities for capturing knowledge, reusing data, and sharing information are major barriers to achieving the goals above. Data needed by collateral and downstream project functions is too often unavailable, outdated, or captive to error-prone manual methods of dissemination and re-entry to aid product development as fully as they would like. At every company we’ve studied, better management of simulation data and processes is a key objective – many explicitly call out “PDM for CAE” as their biggest need to get more value from the technology.

What do practitioners seek, above all? The ability to:

• Have confidence that a simulation is based on the current, correct product configuration
• Easily use output from one analysis discipline as input to another
• Readily retrieve past simulation models, processes and results for easy and confident interpretation, re-execution or modification – even months or years after the original work was done

Beyond this, we hear that the value of simulation data/process management will be greatest if embedded in the context of broader product-development capabilities:

• Configuration management, product structure management
  • For coordinating CAD geometry and CAE models and processes. This is needed for two kinds of new-product development work processes:
    • CAD-led
    • Analysis-led
  • For coordinating simulation models and results with corresponding matrices of product variants, such as in automotive and commercial vehicle development
• Change management, workflow management – to ensure:
  • Geometry changes trigger timely re-analysis
  • Analysis results are fed back to product development, and acted on
• Requirements management – to help ensure:
  • System-level performance targets adhere to program requirements
  • Adherence is maintained as system-level targets are cascaded down to subsystem and component-level performance targets
• Project/program management – for managing:
  • Controlled data sharing as determined by partner trust levels
  • ITAR compliance
  • Schedule adherence
• Document management – to associate simulation data with, or incorporate it into, documents such as those mandated by regulatory agencies
• Management reporting