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Achieving faster time to market with advanced tolerance analysis software

Sigmetrix tolerance analysis can improve manufacturing.

Sigmetrix tolerance analysis can improve manufacturing.

With the ever-increasing need to produce better products more quickly and at a lower cost, product design teams demand innovative simulation technologies to understand how a product will perform in before parts are made. The Computer-Aided Engineering industry is therefore one of the fastest going segments, but these tools also fall under the same scrutiny – they must be fast and easy to use. Engineers can’t wait days or even weeks for analyses to be performed before receiving the information they need. For example, tolerance analyses can provide valuable information about the probability of having designs that work using existing manufacturing capabilities as well as help evaluate different design options. But as tasks typically performed near the end of the design cycle with the aid of spreadsheets, their value is too limiting.

Sigmetrix, a company dedicated to helping customers produce better products through mechanical variation management, offers software tools that work directly with the design models, including embedded tolerance data when available, to provide design teams necessary information early in the design process. Sigmetrix has emphasized speed and ease-of-use in their tools, and they supplement them with a strong portfolio of training courses in both concepts and software, ensuring their customers have what they need to use them effectively. In the space of mechanical variation management, their training and software solutions span from addressing the most basic designs to the complex.

Their approach is working. When Hilliard Corporation identified short-comings and inefficiencies of their traditional methods for managing variation – spreadsheets manually populated from drawings, they used CETOL 6σto evaluate a legacy field issue caused by complex angular tolerances not captured by their traditional approach. Their conclusion? Not only did the software identify the problem much more quickly, but had it been used during development, the problem would have never occurred.

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