Tolerance Stack Up Analysis: Parameter Sensitivity and Optimization
In this step, we explore the concept of design sensitivity, showing how small variations in input can lead to significant changes in output, and how that affects the predictability and robustness of your design. Through practical examples and hands-on demonstrations, you'll learn how to reduce sensitivity and improve performance, while keeping manufacturing costs under control.
See episode 4 of the "How to set up a tolerance stack" series
Understanding sensitivity and input-output relationships
Sensitivity reflects the impact of input variation in the output of your design
• Neutral; input variation = output variation
• Sensitive design: a given input -> high variation of the output
• Robust design: a given input -> low variation of the output
Example of sensitivity: Lever arm and syringe
Two syringes with same nominal dose can have very different accuracy levels depending on their geometry.
• Sensitive design = short stroke and big diameter
• Robust design = long stroke and small diameter
• In the syringe example – both cases have the same input; but a very different output
Improving stability by increasing the distance between rotational locks
• Placing constraining features far apart = robust design: low angular sensitivity
• Placing constraining features with small distance = sensitive design: high angular sensitivity
Dimensioning: use smaller dimensions
• Smaller dimensions = lower variation
• Larger dimensions = higher variation
Absorbing variation with long, soft springs
• Springs with lower stiffness → lower sensitivity to variation
• Springs with greater stiffness → higher sensitivity to variation
• Note: a spring with lower stiffness require more pretention to obtain the same force
Reducing variation by simplifying your tolerance stack
• Sensitive design = many dimensions/parts in a tolerance stack
• Robust design = few dimensions/parts in a tolerance stack
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