In an earlier article in this series, I introduced some basic issues in measurement systems analysis such as granularity, accuracy, reproducibility, repeatability, stability and linearity. In this article we will explore in more detail how to evaluate the performance of a measurement system with respect to bias and linearity. Gage bias examines the difference between […]

# Category Archives: Six Sigma

Failure Modes and Effects Analysis (FMEA) is a form of risk analysis that should be applied when designing or changing products and processes. FMEA is a methodical seven step approach to analyzing a product or process for ways that it can fail, and then taking appropriate actions based on this information. We will explain the […]

A metric that is commonly used in Lean Six Sigma is Overall Equipment Effectiveness, or OEE. OEE can be used to help target key areas for improvement. It is a way to measure equipment performance in three major areas where losses or waste may occur. Although OEE is most commonly applied in manufacturing, it can […]

Earlier in this series I introduced the topics of Process Capability and Process Control. You may wish to review that article before reading this one. I recently received the following query from one of my Green Belt students: “In my company our manufacturing process has a lot of special variations which makes the process very unpredictable. […]

In a previous article in this series we discussed a number of tools that can be used to do a better job of capturing the Voice of the Customer regarding requirements. Today we will look in more detail at one of those tools, the Kano Model. This model was developed by Dr. Noriaki Kano, a […]

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 […]

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 […]

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 […]

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 […]

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. […]