Statistical Thinking vs. Engineering Thinking

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Thinking of the core concepts of quality and statistical process control we consider statistical thinking vs. engineering thinking.

Engineers have it made. In the world of engineering, the formulas are precise and definitive. When products are designed, the dimensions are exact, the calculations are accurate, and the resulting characteristics are known.

Manufacturing is an application and is not so precise. Variations can occur anywhere in the process and are often hard to predict accurately. People work with items that were intended to be two inches long, but in reality they are anywhere from an eighth of an inch too big to an eighth of an inch too small. To use and old adage, two plus two seldom equals four.

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This has frustrated managers worldwide for a long time. As engineers we may predict the output of a process and wonder why things didn’t turn out as planned. The problem is in the definition of what should be. Statisticians have addressed this problem by developing methods for calculating expected results which take variation into account. Their methods call for observing the process in its actual environment so the expected variability can be measured.

So how do we observe the process?  Enter Walter Shewhart…

In the 1930’s, Walter Shewhart devised a way to predict what could happen during a production process. His technique involved collecting
observations from the shop floor, running calculations on this data and then plotting it on a graph. Based on statistics of what had happened in the process, he could predict what would happen in the future. Comparing the actual result to his prediction was a simple matter of plotting points on graph paper. His graphs became known as the Shewhart Control Charts. They were and are used to control the output of manufacturing processes.

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This content is adapted from Zontec’s The Book of Statistical Process Control.  You can download a free copy here.