Let me clarify my posting.
I assumed the following: the data collected came from one process stream feeding 5 nests (test stands) and the 150 parts were consecutive.
Or, the data collected came from 5 process streams feeding 5 nests (test stands) and the 30 parts to each nest were consecutive.
The first thing which I do with data is to plot it on a Normal Probability chart. [It is easiest chart to produce quickly which will provide clues to the process measurements quickly.]
In the case presented, the Normal Probability chart suggests that each nest is measuring a process which has at least a tri-modal distribution with the higher and lower modes having some type of physical or mathematical boundary. The middle mode appears to have a normal distribution. Additionally, the data from each stand, while producing similar distribution trends, has much variation in their median and spread values. [Note: There was no mention of rational sub-grouping or process analysis.]
I continued my analysis with run charts to determine if there was any obvious pattern. No specific pattern was observed based upon quick visual analysis, therefore, I created preliminary "control charts" for each nest.
The preliminary "control charts" show a tendency in each nest to have a process component which displays that the highest "tri-mode component" value is skewing the spread (stdev) displayed on the chart.
Based upon this brief and very limited knowledge of the process being analyzed, I concluded he process producing the data values was not understood and, therefore, I classified it as "unstable" for effect.
[I.e.: If you don't know what it is, then do not assume the easy, standard solution.]
Since I could see at least a tri-modal with some type of upper and lower limiting distribution, I classified it as "non-normal," again for effect.
I am sorry that my first posting was so curt, but most posters are looking for a "give me a number to use" solution for which I have little patience. I use their postings for analysis exercises only. I do not wish to provide thorough solutions to those unwilling to study and understand the application of basic "statistical control." Art Binder would kick me out of his office many times until I could and would show him my data analysis (no numbers only/number cranking analysis.) I do not provide commentary on the finer methods of control charting until I know that the receiver has a good understanding of the basics.
As for bar graphing data and placing a "bell curve" over it, again I will say, there are major flaws in this type of analysis. The bucket size (value width and center placement) is more art than science and the eye will tend to believe the bars fit a bell shape if it is imposed making it appear normally distributed. [Poor graphs can be misleading. Look at the many examples on business scorecards not based upon statistical rules as noted above, such as month-over-month or year-over-year percentage changes.]