Tolerance Stack-Up Analysis: Parameter Sensitivity and Optimization
In this step, we explore the concept of design sensitivity, showing how input variations 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 tolerances (manufacturing costs) under control.
Series: How to setup a tolerance stack.
Episode 4: Parameter Sensitivity and Optimization
Lower the slope to achieve robustness
Sensitivity is represented by the slope of the curve when you plot the input parameter and the output.
• Neutral ("45 degree slope"):
input variation = output variation
• Sensitive design ("steep slope"):
input variation --> high variation of the output
• Robust design ("low slope"):
input variation --> low output variation
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
Best practice: use smaller dimensions
When designing interfaces between parts - size matters. Smaller dimensions is easier to keep in control (smaller tolerances). Keep that in mind if you are in the quest for low variation.
Small dimensions = small tolerances = lower variation
Larger dimensions = large tolerances = higher variation
Best practice: use 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
Tip: the same goes for parts or compliant mechanisms (if you consider part stiffness as springs you will get the same results)
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