35% Increase in Productivity Using 6SigmaET

7 August, 2017

Renowned test and measurement equipment designer Rohde & Schwarz GmbH & Co KG recently presented a comparison between 6SigmaET and another, market leading, thermal simulation software. The comparison showed that in 7 out of 12 cases 6SigmaET could solve models that were not possible using the alternate software, despite heavy simplification. Rohde & Schwarz also reported an overall 35% increase in project efficiency, in terms of time, through using 6SigmaET.

rohde and schwarz

The presentation, given at the 6SigmaET German user meeting in Friedewald, concentrated on time taken to prepare, build, solve, post-process and run multiple iterations of the model to ‘benchmark’ 6SigmaET against market leading thermal simulation software. In total, 12 cases of varying size and complexity were shown.

Of the 12 cases discussed 7 could not be completed using the market leading software; all 12 were possible with 6SigmaET. Of the remaining 5 cases which were possible to solve in both pieces of software, it was reported that some degree of simplification – in most cases ‘strong’ simplification – was required when using the market leading software; a high level of detail, including full CAD model and PCB design, was retained using 6SigmaET. Despite the differing degrees of complexity, 6SigmaET performed faster in 4 out of 5 cases, with the fifth case being a dead heat. In one example, it was quicker to run a baseline and three further iterations in 6SigmaET than it was to solve the baseline in the other software.

The 7 cases that could not be solved using the market leading software all took (or were estimated, based on experience, to take) a minimum of 80 hours before reaching a point where it was not possible to continue.  In one case, it took 85 hours – approximately two working weeks– of an engineer’s time simplifying and meshing a model only to determine it wasn’t possible to go any further. In contrast, using 6SigmaET, it was possible to create a baseline model, solve it, analyse results and repeat this process 6 times for different versions of the model in the same period, whilst maintaining a high level of detail.

For a copy of the full presentation please contact