Predictive engineering analytics

Predictive engineering analytics (PEA) is a development approach for the manufacturing industry that helps with the design of complex products (for example, products that include smart systems). It concerns the introduction of new software tools, the integration between those, and a refinement of simulation and testing processes to improve collaboration between analysis teams that handle different applications. This is combined with intelligent reporting and data analytics. The objective is to let simulation drive the design, to predict product behavior rather than to react on issues which may arise, and to install a process that lets design continue after product delivery.

In a classic development approach, manufacturers deliver discrete product generations. Before bringing those to market, they use extensive verification and validation processes, usually by combining several simulation and testing technologies. But this approach has several shortcomings when looking at how products are evolving. Manufacturers in the automotive industry, the aerospace industry, the marine industry or any other mechanical industry all share similar challenges: they have to re-invent the way they design to be able to deliver what their customers want and buy today.

Products include, besides the mechanics, ever more electronics, software and control systems. Those help to increase performance for several characteristics, such as safety, comfort, fuel economy and many more. Designing such products using a classic approach, is usually ineffective. A modern development process should be able to predict the behavior of the complete system for all functional requirements and including physical aspects from the very beginning of the design cycle.

In view of cost or fuel economy, manufacturers need to consider ever more new materials and corresponding manufacturing methods. That makes product development more complex, as engineers cannot rely on their decades of experience anymore, like they did when working with traditional materials, such as steel and aluminium, and traditional manufacturing methods, such as casting. New materials such as composites, behave differently when it comes to structural behavior, thermal behavior, fatigue behavior or noise insulation for example, and require dedicated modeling.

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