Recently, I wrote about the process capability index and tolerance interval.

The four common capability and performance indexes collectively contain all of the summary information about process predictability, process conformity, and process aim that can be expressed numerically.

In May 1924, Walter Shewhart wrote a memo that contained the first example of a process behavior chart (i.e., a “control chart”). It was a chart for individual values that would be known today as a p-chart.

Walter A. Shewhart is lauded as the Father of Statistical Process Control (SPC) and is perhaps best remembered for the SPC control chart.

One hundred years ago this month, Walter Shewhart wrote a memo that contained the first process behavior chart. In recognition of this centennial, this column reviews four different applications of the techniques that grew out of that memo.

In less than two months we will celebrate the 100th anniversary of the invention of the control chart, a tool most often associated with statistical process control (SPC). Considering SPC from our modern perspective made us ask, “Is SPC still relevant?”

When presented with a collection of data from operations or production, many will start their analysis by computing descriptive statistics and fitting a probability model to the data. But before you do this, there’s an easy test that you need to perform.

Over the past two months we’ve considered the properties of lognormal and gamma probability models. Both of these families contain the normal distribution as a limit.

Clear thinking and simplicity of analysis require concise, clear, and correct notions about probability models and how to use them.

So far in this series our focus has remained on statistical process control (SPC) in manufacturing.