Simulation-driven design can help engineers design complex products, but there are many ways to implement it.

Simulation-Driven Design: Feasible or Fallacy?

May 18, 2020

by Chad Jackson

Today’s engineers are in a tight spot. From smartphones to conveyor belts and coffee pots, today’s products are increasingly complex. They often meld mechanical and electrical functions with software code. To meet performance requirements, engineers must take many more factors into account during design than ever before. And, of course, do it fast while keeping costs low.
 
Balancing all this is no easy task. Simulation-driven design can help.
 

What is Simulation-Driven Design?

 
Traditionally, simulation is the final step in product development. Engineers use analyses to validate a design after it is nearly finished. By that time, the design is mostly set. Validation may highlight problems and offer potential modifications, but the overall design does not change much.
 
Simulation-driven design moves simulation much closer to the front end of the process. Engineering teams do not have to wait until they have completed a design for analysis and feedback. Instead, they analyze as they design, enabling them to assess how a design affects function quickly. This provides immediate, vital feedback to guide design decisions. It also frees them to experiment, so their final designs are more innovative while still meeting all specifications.
 
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Companies that use simulation-driven design dramatically accelerate design cycles. They also avoid extra rounds of prototyping and testing and reduce the number of post-release change orders that often disrupt other or new design projects.
 
Simulation-driven design does not replace the final expert analysis needed to verify performance at the end of the process. But it does enable engineers to optimize designs and test solutions as they design, rather than waiting to hear back from analysts after they have completed a design.
 
Simulation-driven design makes a compelling case. Yet implementations of this powerful tool can vary dramatically. Let’s look at three major ways to do it.
 

Hybrid CAD-CAE, Engineer-Led Analysis

 
In this approach, engineers develop and run the simulations with tools that offer a mix of computer-aided design (CAD) and computer-aided engineering (CAE) capabilities. The software lets them develop the geometry of their designs, analyze performance, and make modifications in loops.  After making those changes, they can run more simulations and continue with iterations until they have developed, and perhaps even optimized, their design.
 
Engineers need little to no training to use these analysis capabilities. Granted, their simulations are simpler and more directional than the formal, highly detailed simulations usually run by analysts. Still, they do not have to wait for analyst feedback, so the design process is faster.
 
Engineer-led analysis gives designers the most freedom, but it also requires them to have the knowledge and skills to build and analyze their designs.
 

Application-Specific Tools, Engineer-Initiated Simulations

 
In this approach, engineers conduct analyses with specialized, application-specific tools. The app is built by expert analysts to set up and run one particular simulation, such as noise, vibration, and harshness of an engine.

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These apps leverage automation and standardized inputs to produce a repeatable, highly accurate analysis. They make it easy for engineers to plug-in data and see results. The tradeoff, however, is that these apps will not run any other type of simulation. They are inflexible, purpose-built for one scenario, though engineering teams could build dozens and dozens of additional apps, each for a different scenario.
 

Template-Based, Workflow-Automated, Analyst-Initiated Simulations

 
This approach also uses specialized app-automated tools, but in this case, those capabilities are built for analysts. The purpose is not to simplify anything. Instead, it is on automation and speed. Expert analysts can throw designs at these template-based apps, walk away, and come back in a few hours for the results. Equally important, they are confident of the results because the apps have been optimized to solve their specific scenario.
 
In this approach, engineers are not the only ones employing simulation earlier in the process—the analysts are, too. These apps increase their bandwidth, so analysts have more time to participate earlier in design. App automation lets engineers hand analysts their designs earlier in development and still get feedback super-fast.

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Which Approach Works Best?

 
Frankly, there is no clear winner. The fit depends on the organization’s design needs. Two of these options require more time from engineers to conduct analyses earlier, which in turn allows them to realize benefits later in the design. The other option places more demand for expert analysts. Companies must decide which method fits their needs. What is clear in this scenario? Simulation should be front-and-center in the engineer’s toolkit.
  
Chad Jackson leads Lifecycle Insights (lifecycleinsights.com), which conducts research on technology-led initiatives for engineering executives.

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