Performing action...

Implementing the Process
Effective implementation of simulation-driven development begins with establishing a baseline consisting of your own existing product, or that of one or more competitors. Products are tested to build a quantitative knowledge base of information on product behavior that will be critical in correlating the analytical and physical, and in providing empirical data where computer modeling is impractical. In this case, hybrid models are built combining virtual models and test data to accurately represent the system. Once this baseline is established, various components and subsystems can be modified to evaluate multiple alternatives before beginning the detailed design process.

An important aspect of establishing the baseline is Customer Usage Profiling (CUP) In a typical CUP program, products fitted with instrumentation and data-collection gauges are provided to customers for use over an extended period of time. This indicates, often with surprising results, how products are actually used, and abused, in the real world. For example, the armrest in a car is designed to support the weight of an arm, but will it safely support the weight of a child climbing into the back seat or a bowling ball tossed into the car? How much force can be applied before a knob being turned in the wrong direction breaks? Is the current mirror on the motorcycle over-designed? Can a lighter, cheaper material be substituted? CUP saves warranty, liability, and material costs by making sure components are neither under nor over designed.

Customer usage profiling and related load and duty cycle definitions serve as a foundation for overall product target setting, where goals for overall performance and functionality are established. Targets are based on CUP requirements, competitive benchmarking, and product features deemed necessary to strengthen market share and brand image. These product system targets are then cascaded to bring the dynamic loading and duty cycles to individual parts, allowing engineers to evaluate reliability and durability and achieve very good first design of the geometry and material at the component level.

With these increased levels of simulation being performed in meeting the various targets, orders of magnitude more data and document files are generated than in the more traditional development processes. The resulting need for up-front data management is critical in terms of information sharing, data quality, security, and collaborative capabilities via the Internet. Thus, companies getting into simulation-driven development need to define requirements and build the information platforms they need for this advanced work.

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