We tied up last year in a neat little bow, talking about how stories define ourselves and our work; waste is waste, no matter your political leanings; and putting numbers from the news in context.

The control chart is at the heart of the very definition of quality. It is central to building, maintaining, and predicting quality into the future. However, control charts today, more often than not, are misused and misunderstood.

As the global economy grows, it’s more necessary than ever to stay on top of efficiency. Keep up with increasing production demands by implementing a continuous improvement method to streamline the workflow.

Last week I joined the New England Idea Generation Consortium (NEIGC) on a tour of the Stone Zoo where we had the opportunity to see how continuous improvement is expressed in an animal-care f

Iam not really sure how it started, but one day a couple months ago, I found myself diving down an internet rabbit hole in search of more information on a guy named Alfred Adler.

Everybody wants to design and conduct a great experiment! To find enlightenment by the discovery of the big red X and perhaps a few smaller pink x’s along the way.

In this article I will show that the conventional method for calculating uncertainty is not always reliable.

Walter Shewhart, father of statistical process control and creator of the control chart, put a premium on the time order sequence of data.

Even though most businesses have invested in quality management and performance improvement, each organization is unique. People, processes, and machines must be coordinated to achieve desired outcomes. This is not easy.

The frequently referenced learning pyramid asserts than an average student retains 75 percent of information learned through practice, compared to just 5 percent of what he hears in a lecture.