It helps us determine whether your sampling and/or subgrouping approach is rational (appropriate to the process). Given your process, I would expect minimal variation within an order (setup), but much more variation between orders (setups). Your process would be setup dominant, with some potential impact from material lots.

Before ask you about sampling and subgrouping it will help you describe a little more.

The process is for seamless tube. For example you get the first billet with diameter of 50mm and with a series of machines goes 40 mm -> 30->20-> 12 mm (final machine) and then goes to annealing and QC received a sample 1/1000 kg.

Usually the specifications is at the last machine and at previous machines you have targets in order to watch the process.

From production we have only measurements such as diameter, wall thickness, length, weight.

In QC we have these but also Rm, Rp0.2 Rp0.5 expansion etc, measurements that production don't have the necessary equipment.

For the common measurements QC take at least one sample to confirm those.

Also for an order of 1000 kg production will measure 6 common characteristics (diameter, etc), QC will measure just 1.

For one machine in each shift will have at least 10 or more orders. Each order have different specifications.

Multiple the above by 8 (machines).

In conclusion the majority of common measurements it will received from the production.

I would like to ask consider the above and the tables that i attached, what statistical checks would you perform ( Cp, CPk Anom, Anova)?

What would be the suggestions about the sampling?

Entails what are the minimum requirements?

Thank you in advance