Something that sets Hawley Martin apart from much of our competition is our association with The Oaklea Press, a book publishing business that specializes in titles meant for business leaders engaged in continuous improvement and lean transformation.
One reason manufacturing businesses go lean is to achieve Six Sigma. Six Sigma is a reference to the level of quality produced in a manufacturing process. Most traditional companies believe that 99.9% good quality is a terrific achievement. Perhaps by historical standards it is. However, consider what 99.9% good quality would mean in everyday life in the United States:
Unsafe drinking water once per week; No electricity for nearly one hour per month; 500 wrong surgical procedures per week 2 short or long landings at most airports each week; 20,000 wrong drug prescriptions per year; 2,000 lost articles of mail per hour.
Perhaps 99.9% is not so good, after all.
World class companies ship products to their customers with 99.99966% good quality. From a statistical point of view, this means that they are shipping Six Sigma quality–no more than 3.4 parts per million defects. This’s nearly zero. The term six sigma (also written 6 [Greek Letter for Sigma], using the lower case Greek letter for sigma), refers to the number of standard deviations away from the mean (or average) point in a bell curve (also known as a “normal distribution”).
For readers who are not statisticians, the bell curve is a natural phenomenon experienced in large populations of almost anything. Imagine, for example that you are harvesting corn. The size of most of the ears will be centered around the mean (average) of the population. A few ears will be moderately large and fewer still will be very large. The same relationship appears in the smaller sizes–a moderate number are smaller than the mean, and a still smaller number are very small. If a million ears are harvested, only three to four ears will fall in the very largest category (six sigma from the mean) and only 3-4 ears will fall into the smallest category (six sigma from the mean in the other direction). The size of all the other ears will fall into a “normal distribution” as defined by the bell curve shown below in the illustration that accompanies this article.
This same relationship tends to hold for populations of people. If the height or weight of a large population is measured and plotted on a graph, the statistics will fall into the classical normal distribution. In manufacturing, the naturally occurring variations in processes will also tend to fall into a normal distribution, for example, the dimensions of stamped or injected-molded parts, the thickness of plating, or the amount of solder on a printed circuit board.
Achieving six sigma delivered quality to the customer is not an easy feat, especially considering the rolled throughput yield where the yields of each sequential processes are multiplied together to compute the final yield (the percentage of good parts produced by a given process). For example, if there are four processes, each with a 99% yield, the rolled throughput yield is (0.99)x(0.99)x(0.99)x(0.99) = 96%. So how do world class companies achieve such a small amount of defects delivered to the customer? A combination of methods are used that ensure that a defect is rarely passed on to the next stage of production. A book published by Oaklea Press, Lean Transformation: How to Change Your Business into a Lean Enterprise, covers most of them in detail. Click here to learn more.