Steve Beeler

You have a goal…I have a way to get you there.

Common Cause

Great Books

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Great Books

After a crazy busy summer with the FF50th, I am finally moving into my home office. In addition to finding my slide rule, I have rediscovered so many great books! Here are three great books from my personal library:

The Goal

 

The Goal by Eliyahu Goldratt. The first book on Theory of Constraints. Very cleverly written as a novel, not as a text book. “In isolation yes, in combination no” is a lesson that I apply (successfully and profitably) over and over again.

Out of the Crisis

Out of the Crisis by W. Edwards Deming. Deming’s values and clear thinking provide timeless direction. Correctly categorizing variation (common cause vs special cause) keeps me out of a lot of trouble.

Getting to Yes

Getting to Yes by Roger Fisher and William Ury. This is a great book on how to get things done: focus on common interests, create win-win options, consider alternatives. Don’t leave home without a BATNA!

What great books are on your shelves?  Click on the GET IN TOUCH button below.

Common Cause vs Special Cause

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All manufacturing and business processes contain many sources of variation. The differences may be so small as to be difficult to detect, but they are there. To successfully reduce variation, its sources must first be understood (common cause vs special cause). Less variation, less waste, more profits.

Common Cause vs Special Cause

Common Cause vs Special Cause

Common cause variation is a constant system of chance. The sources of common cause variation are many in number but small in size. A process characterized by common cause variation is in a state of statistical control: its output is stable and predictable. The magnitude of common cause variation can be measured using control charts. The sources of common cause variation can be identified and quantified using Design of Experiments, regression analysis, and other statistical methods. The reduction of common cause variation requires actions on the system.

Special cause variation affects processes in disruptive and unpredictable ways. The sources of special cause variation are relatively few in number but are large in size. A process driven by special cause variation is neither stable nor predictable. Special causes can be detected using control charts through out-of-control signals. The elimination of special causes requires local action on the process. Although special causes account for less than 20% of total variation in most processes, they must be removed before common cause variation can effectively be reduced.

Statistical control is not a natural state. All processes are under relentless attack from special causes.  Confusing common causes and special causes results in one of two mistakes:

(1) The first mistake is to assume variation to be a special cause when it is in fact common cause. The mistake of over adjustment leads to more variation and time wasted looking for a reason for a defect when there is no single assignable cause.

(2) The second mistake is to assume variation to be common cause when it is in fact special cause. The mistake of under adjustment is a lost opportunity to find and eliminate a special cause. Special causes are not always present so it is best to start looking for them right away before the trail grows cold…