Content By Scott A. Hindle

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By: Scott A. Hindle

In everyday language, “in control” and “under control” are synonymous with “in specification.” Requirements have been met. Things are OK. No trouble.

“Out of control,” on the other hand, is synonymous with “out of specification.” Requirements have not been met. Things are not OK. Trouble.

Using this language, an obvious axiom would be: Take action when the process is out of control.

The everyday use of in and out of control is, however, unfortunate for control charts, the major tool of statistical process control (SPC). Why? Because in SPC these terms speak of processes as being stable or unstable. To characterize a process as stable or unstable, process limits, from process data, are needed. Specification limits are not needed.

Given the easy-to-understand basis for the action of meeting or not meeting requirements, coupled with the risk of confusion over the terms in control and out of control, why use control charts? If you are curious to see some of the benefits in doing so, read on. Two case studies are used.

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By: Scott A. Hindle

‘Process Capability: What It Is and How It Helps,” parts one, two, three, and [Read More]

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By: Scott A. Hindle

Walter Shewhart, father of statistical process control and creator of the control chart, put a premium on the time order sequence of data. Since many statistics and graphs are unaffected by this, you might wonder what the fuss is about. Read on to see why.

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By: Scott A. Hindle

I recently got hold of the set of data shown in figure 1. What can be done to analyze and make sense of these 65 data values is the theme of this article. Read on to see what is exceptional about these data, not only statistically speaking.


Figure 1: Example data set.

Scott A. Hindle
By: Scott A. Hindle, Donald J. Wheeler

In theory, a production process is always predictable. In practice, however, predictable operation is an achievement that has to be sustained, which is easier said than done. Predictable operation means that the process is doing the best that it can currently do—that it is operating with maximum consistency. Maintaining this level of process performance over the long haul can be a challenge. Effective ways of meeting this challenge are discussed below.

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By: Scott A. Hindle

In all walks of life, being wrong can come with a penalty. It’s also true that, if you’re lucky, you sometimes get away with it without anybody being the wiser. To understand what this means in relation to the capability indexes Cp and Cpk, read on.

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By: Scott A. Hindle


A t the end of part three of this four-part series on process capability, Alan was ready to identify a contact at the factory who could assist in providing some context around the collected data and the overall production process.

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By: Scott A. Hindle

Part two of this four-part series on process capability concluded with Alan just about to meet Sarah for a second time. He thought he was making good progress with his analysis of Product 874 data until he was asked to assess process capability, even though it can’t be assessed for an unstable process.

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By: Scott A. Hindle

In part one of this four-part series, we considered the basics of process capability, as witnessed through the learning curve of Alan in his quest to determine the product characteristics of the powder, Product 874. We pick up with Alan here as he prepares for his second meeting with his colleague Sarah, to discuss his preliminary results.

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By: Scott A. Hindle

In my August 2015 article, “Process Capability: How Many Data?” I discussed whether 30 data were the “right” number in an analysis of process capability. In this four-part series, the focus is on understanding what process capability is and the pitfalls associated with it, along with how it can help manufacturers develop process knowledge, reach better decisions, and take better actions.