The Practical Optimization of Mechanical Systems in Motion (or How to Build a Better Catapult)

By Christian Kelley

Simulating and optimizing systems or assemblies in motion is a difficult thing to do. Moving assemblies act in a non-linear fashion, and the interplay of all the variables is very difficult to predict. At least that’s what Brant Ross from Siemens Solution Partner PLM MotionPort just told me.

Take the example of a catapult throwing a projectile. With a couple of variables such as angles of the linkage and mounting point of the spring, the path of the projectile becomes very difficult to predict. This is where NX and Recurdyn save manufacturers time and money. Using software to predict and optimize these assemblies is mission critical not only for manufacturers of medieval siege engines, but for manufacturers of anything with moving parts. I don’t pretend to understand half of what I heard in this session; but I do understand the importance of digital simulation and optimization. Companies can’t afford to build thousands of prototypes to experiment on. And this is where tools from Siemens PLM and our partner ecosystem save our customers time and money (and rocks).

Check out some of the information on NX Simulation.

And here’s a link to our partner MotionPort’s site. They are doing some cool things with optimization of mechanical systems.

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This article first appeared on the Siemens Digital Industries Software blog at