# Yearly Archives: 2015

## The Theory of Constraints and Six Sigma

When practicing Six Sigma or any other form of process improvement, it is important to focus improvement efforts where they will do the most good. Of all of the things that we could work on, what should we work on in order to return the most benefit to the organization and the customers of the […]

## Shainin Methods

Previously we discussed Taguchi Methods as an alternative to classical Designed Experiments. Another approach to experimentation is Shainin Methods, as developed by Mr. Dorian Shainin and strongly advocated by Mr. Keki Bhote. The late Dorian Shainin began introducing a series of experimentation techniques in the 1930’s and continued his work for nearly 50 years. Keki […]

## Taguchi Designed Experiments

Classical Designed Experiments (DOE) were discussed in a previous article in this series.  In the last article we discussed descriptive statistics that describe the center of an output or response (mean, median and mode) and the amount of variability in the output or response (range, standard deviation and variance). Taguchi Designed Experiments are an alternative […]

## Descriptive Statistics

In the Analyze phase of Six Sigma, we take the data that we collected in the Measure phase and try to make some sense of it.  We use statistical thinking and analysis to prove or disprove our hunches about what is going on in a process, and to identify the true root cause of a […]

## Estimating Population Parameters from Samples – Point Estimates and Confidence Intervals

In statistics, a data sample is collected or selected from a larger population.  The population includes all of the data that are of interest.   Populations are often so large that it is impossible or impractical to collect data about the entire population.  We therefore rely on samples to make inferences or estimates about the population.  […]

## Designed Experiments – A High Level Introduction

In an earlier article, I discussed the transformation function Y = f(X), where Y represents the output of a process.  The output is a function of the inputs (the X’s) that affect the output. Designed Experiments are used to help us quantify the effect that the inputs have on the output of a process.  In […]

## Is Six Sigma the only way to improve?

When training and coaching Six Sigma professionals, one of the topics that I encourage folks to think about is whether or not Six Sigma is the only path that should be followed by an organization that is seeking to improve their operations.  In our Green Belt program I ask students to choose one side or […]

## The Transformation Function: Y = f(X)

Six Sigma is focused on improving the performance of processes.  In simple terms, processes have inputs, activities, and outputs.  The process activities transform the inputs that come from suppliers into a product or service that is delivered to a customer. Consider baking a cake.  The inputs are ingredients such as eggs, flour, milk, butter and […]

## Statistical Software – A Trap for the Unwary

Statistical software is widely used in practice to conduct various statistical tests and to generate various graphs and charts.  In our Six Sigma courses we use Minitab, which has been under continuous development since 1972 and is one of the most widely used statistics packages.  There are many other fine products on the market as […]

## The Platinum Rule

The Golden Platinum Rule You have heard it say, “Treat others as you would want to be treated”. However, in project management, we replace this Golden rule with the Platinum rule. It says, “Treat others as they want to be treated”. Organizational theories teach us that we are all different. Theory X and Y, for […]