Suppose we want to design a single attribute sampling plan so that

- a good lot with a defective rate of 2% will be accepted 95% of the time , and
- a bad lot with a defective rate of 10% will be accepted 15% of the time .

In other words, we want to find an attribute sampling plan whose *OC* curve passes through the two points (0.02, 0.95) and (0.1, 0.15). How can we design a plan (i.e., choose appropriate values of *n* and *c*) that satisfies these criteria? We suppose that the lot size is large as compared with the sample size, so the Binomial approximation suffices. We could use a mathematical approach (Wetherill, 1969), but we can also make use of the Spin Button to design the desired sampling plan.

Here is the spreadsheet for designing a sampling plan (*n*, *c*) for (0.02, 0.95) and (0.1, 0.15). As before, you can **click on the chart** to get to the Excel environment. Use the Spin Button to change the values of *n* and *c*. You will see that the acceptance number has a much greater effect on the *P _{a}* and hence the shape of the

After experimenting with values of *n* and *c*, you should find that the sampling plan which has an *OC* curve approximately passing through the two points (0.02, 0.95) and (0.1, 0.15) is *n* = 61, *c* = 3.

Journal of Online Mathematics and its Applications