SWOT Analysis is a methodology for the team to explore the Strengths, Weaknesses, Opportunities, and Threats of an item, or area of interest.

When a team is faced with a condition where they only have available to them small sample sizes (< n = 30) and they want to find the difference between two means, they would use a t-test based on the t distribution. (also known as student t distribution). To compare the difference between two means using a t-test is much like the method for using larger samples, however for small sample sizes; we need to use the t table for critical values instead of the Z table for the normal distribution. So, samples >30, use the Z table. For samples <30, use the t-table. Refer to the lecture for more on this.

In the war on waste, the team needs to understand the customer demand rate. Think of a metronome (the ticking, swinging tool used by musicians to maintain constant timing). The metronome can be adjusted to different beats per minute. Takt Time is similar to the metronome. The team can adjust the takt time if it knows the average consumption rate of customer demand. If the rate of making a product is slightly faster than the takt time, there is very little built up inventory; hence minimal waste. If however, if it team ignores takt time, they are in danger of not having enough capacity to keep up with demand or too much capacity will be produce stacked up inventory. If there is inventory, there has to be a place to put it. There is a cost associated with that space. If there is inventory, it also has to be moved. There is a cost associated with that movement as well, and so on.

A test statistic is calculated. The test statistic is compared to a critical value (found in a table). If the calculated test statistic is beyond the critical table value, the null hypothesis is rejected. If the test statistic is not beyond the critical value, the null hypothesis has not been rejected (i.e., failure to reject the null hypothesis)

This type of testing using a test statistic is used in the f test, the t-test, and the chi-square tests.

Considering that a lean Initiative concentrates on reduction of waste and continuous flow, a team needs to understand the theory of constraints concept. Once the most constraining step in a process has been identified by the team, the idea of theory of constraints is to exploit this constraint to find ways of speeding up that particular step. Once that step has been optimized, the team will find ways to refine the next slowest step, exploit the step, optimize the step, and the process repeats until it’s no longer economical to refine any further.

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.