**Answer:**

**The Type I error that could result from the test is that The test provides convincing evidence that the proportion is greater than 90%, but the actual proportion is equal to 90%.**

**Step-by-step explanation:**

We are given that machines at a factory produce circular washers with a specified diameter.

The quality control manager at the factory periodically tests a random sample of washers to be sure that greater than 90 percent of the washers are produced with the specified diameter.

<u><em>Let p = proportion of all washers produced with the specified diameter</em></u>

So, **Null hypothesis**, : p = 90%

**Alternate Hypothesis**, : p > 90%

Here, null hypothesis states that the proportion of all washers produced with the specified diameter is equal to 90%.

On the other hand, alternate hypothesis states that the proportion of all washers produced with the specified diameter is greater than 90%.

**Now, Type I error states the Probability of rejecting null hypothesis given the fact that null hypothesis was true or in other words Probability of rejecting a true hypothesis.**

So, according to our question Type I error would be that the test provides convincing evidence that the proportion is greater than 90%, but the actual proportion is equal to 90%.