Design Tolerances Based on Economics (Using the Taguchi Loss Function)

Defining tolerances for our quality characteristics is sometimes not an easy task. If we set tight tolerances, it could be costly to make with a lot of rejects and rework in the future. If we’re too sloppy with our tolerances, then it can affect the functionality of our product, leading to unhappy customers, and also possible rework and scrap. There’s economics involved in setting-up tolerances.

Genichi Taguchi related his measure of quality (variation from the target spec) with economics, called the Taguchi Loss Function. It’s used to calculate the cost (in money) of a certain deviation from a target value. It assumes that the farther our quality characteristic is from our target value, the more costly it is to us.

We talk about how we can use the Taguchi Loss Functions as a way for us to set tolerances for our designs. Scroll lower to get an interactive tool and the equations.

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How Many Controls do we Need to Reduce Risk?

When we’ve identified a risk to our design or user process – and that risk can pose a potential harm – how many controls do we need to add?

We discuss prevention vs. detection controls, ALARP, as low as possible, and some scenarios where we could (and maybe couldn’t) justify a risk as acceptable without adding additional controls.

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