Posts in category Six Sigma

TQM has been viewed by some as a program that was popular in the 1980s where the emphasis was on the ‘T’ and the ‘Q’, but not much emphasis was on the ‘M’ — management involvement. And, as such these naysayers have written off TQM as a failed movement. Some, who were immersed into the TQM movement view six sigma in much the same way. Some might say six sigma is just “the flavor of the month”, and if we ignore it, it will go away. If you consider six sigma dates back to the mid-1990s, that flavor has been going on for more than 300 consecutive months. It’s quite a flavor! Many of the tools of TQM are found in six sigma – – especially the statistical tools. The tools are just as powerful now as they were then and TQM did have some major successes. One of the things that differentiate six sigma from TQM is through the use of tollgate reviews. With tollgate reviews, management is not only committed to continuous process improvement; they are actively involved in the projects.

A Tree Diagram is a chart that begins with one central item and then branches into more items and keeps branching until the line of inquiry begun with the central item has been exhausted.

The tree diagram, with its branching steps, motivates the team to move from the general to the more specific in a systematic way. The tree diagram is useful to organize a team’s thinking about an issue so that the main ideas and relationships are immediately apparent.

TRIZ (pronounced TREES) is a Russian technique for problem-solving. The theory was developed from extensive research covering hundreds of thousands of inventions across many different fields to produce a theory which defines generalized patterns in the nature of inventive solutions and the distinguishing characteristics of the problems that these inventions had overcome.

The u chart is used with a varying sample size where you are counting the number of defects in the sample. If you remember, the difference between a defect and a defective is this. A defect can be found on an otherwise acceptable product; whereas, a defective means that the whole item is unacceptable. For example, you might have some minor defects in the fabrication of the windshield. The windshield passes inspection even though there are some minor defects. Defects are still undesirable, but there are an insufficient number of defects to render the windshield unusable. If, however, the windshield is cracked, the windshield would be rendered defective, and totally unusable. With the u-chart, we are looking at defects – not defectives, and remember that were looking at a varying (as opposed to constant) sample size. If it was a constant sample size and we were evaluating defects, we would instead be using a c-chart.

Weibull analysis of failure data using the Weibull distribution is the most often used technique in reliability engineering.

The Weibull distribution can be used to model many different failure patterns and this, along with its relative ease of use, accounts for its extensive application.

There are two ways to make a bad part or make for an unhappy customer. First, if the centering of the variation in a process gets too close to either the upper specification limit or the lower specification limit, a bad part will be produced, or the customer will be unhappy. Secondly, if the variation in the process is centered, but the variation in the process is too wide, no matter how the team tries to center the variation, a bad part will be produced. The process variation overlaps either the upper specification limit or the lower specification limit. The X-bar R Chart monitors the process across time and reveals assignable-cause variation, namely looking out for these two conditions as they arise. The other value of using this chart is that if there is no assignable-cause variation, the process is to be left alone. If adjustments are made to the centering on a process that is exhibiting common-cause variation, more variation will be generated than it would had the process just been left alone. In other words, if the process is in statistical control, leave it alone. For more information, please view the lectures for both types of charts.

The XmR Chart is very similar to the X-bar R Chart in the rationale for its use. The main difference is that the XmR Chart uses individual data points; whereas, …

The Z-score table (also known as the standard normal distribution) is used for larger sample sizes, namely where the population or sample size is greater than n=30. The Z score table assumes a normally-distributed process.

The Z score table is used in various hypothesis tests including tests on single means, the difference between two means, and tests on proportions.

The Standard Deviation of a set of data describes the amount of variation in the data set by measuring, and essentially averaging, how much each value in the data set …

The service world has recognized the value of poka-yoke during the last several years. One way of applying error-proofing (poka-yoke) in the service sector is to devise a “task” poka-yoke. A task poka-yoke concentrates on the tasks that a server must perform and devises methods to assure the task is completed correctly. A popular example of a task poka-yoke is the automatic change dispenser that you encounter in many stores.