Statistical Tolerance Analysis Makes Good Designs Better

Determining optimal tolerances, especially for complex mechanisms

, can make the difference between cost-effective, on-schedule products and those burdened by scrap, rework, and delay. Traditional tolerance analysis often provides too little information as is performed too late. Designers might perform a 1D tolerance stack-up for a few contact surfaces that appear critical, but they usually wait to do this until right before a release to manufacturing. Unless manufacturers understand design intent, changing tolerances during production can result in products that miss customer requirements and cost targets.

The focus of tolerance analysis should be on the mechanism's critical dimensions and parameters. An automotive engine with optimized tolerances will have more horsepower, greater efficiency, and lower emissions than an engine with the same displacement that has not been optimized.

The goal of tolerance optimization is to balance assembly performance against manufacturing costs. Optimization software identifies dimensions that do not affect performance so their tolerances can be traded off to critical surfaces. In this way, tolerance optimization improves product quality without increasing costs. It also streamlines development cycles by requiring fewer physical prototypes.

Tolerance analysis software has a role to play throughout every stage of design. In concept product modeling, it highlights variations in component interfaces that affect design feasibility. In functional assembly modeling, the technology tells engineers which variations in assembly constraints will affect performance in the "as-designed" model. During detailed part modeling, tolerance analysis labels changes in part dimensions that affect performance in the "as manufactured" model. And in manufacturing process modeling, the software identifies manufacturing variations that affect the ability for the part to be produced.

Assumptions made in a tolerance analysis have repercussions throughout development. It is vital to be as precise as possible to avoid expensive errors. But a lot is not known. For example, what are the critical surfaces? What tolerances can machine tools hold? Are the ranges within the capability of current capital assets, or will manufacturing require new technology and tools?

In order for tolerance analysis to be accurate, it needs to be performed as a statistical tolerance analysis. A Basic tolerance stack-up fails to properly account for all variations that can occur during the manufacturing process. Randomized tolerance analysis, such as that used by Monte Carlo, lacks the precision necessary to effectively predict outcomes in manufacturing.

Today, companies all over the world are using statistical tolerance analysis to increase the robustness of their assemblies. Medical device companies such as GE & Medtronics, automotive companies such as Audi, Fiat and Porche, along with heavy industry, electronics and consumer goods companies are all moving to the more precise methods of tolerance analysis to lower costs and increase quality.

by: Sigmetrix

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