Chew Jian Chieh

Consider a production process that produced 10,000 widgets in January and experienced a total of 100 rejected widgets after a quality control inspection (i.e., failure rate = 0.01, success rate = 0.99). A Six Sigma project was deployed to fix this problem and by March the improvement plan was in place. In April, […]

The two-sample t-test is one of the most commonly used hypothesis tests in Six Sigma work. It is applied to compare the average difference between two groups. You use it to determine if the difference is significant or if it is due instead to random chance. It helps to answer questions like whether […]

What is Gage R&R? Like it or not, any process is going to have variances and the potential for defects. Measurement error is unavoidable. There will always be some measurement variation that is due to the measurement system itself. Most problematic measurement system issues come from measuring attribute data in terms that rely […]

It is a common scenario: A practitioner has sales data for the past several months and wants to forecast next month’s sales volume. This type of forecasting can help manufacturers and distributors ensure they have enough product to meet customer demands. But how is this forecasting done? Statistical analysis software offers two ways to plot […]

What is the usual way most people go about solving problems? Most people and organizations consciously or unconsciously use this method, as illustrated in Table 1 below. Table 1: Normal Method of Problem Solving Step Example 1. Understand what is to be improved and set a goal I am too fat. I want to reduce […]

In some situations, Six Sigma practitioners find a Y that is discrete and Xs that are continuous. How can a regression equation be developed in these cases? Black Belt training indicated that the correct technique is something called logistic regression but this tool is often not well understood. An example about a well-known space shuttle […]

Estimating potential improvement project benefits unfortunately have not always been subjected to same level of analytical rigor that practitioners insist on applying in typical Six Sigma work. The fault lies in the lack of an analytical methodology. Project teams can help themselves over this hurdle with a straightforward method for calculating potential and actual benefits. […]

The fishbone diagram is the most commonly used cause-and-effect analysis tool in Six Sigma. Cause-and-effect analysis is one of the key tasks in any Six Sigma DMAIC project because half of the game is won when the correct root causes of the problem (the Y) are found. However, poor use of the fishbone diagram is […]

At its core, Design for Six Sigma (DFSS) is concerned with the accurate translation of what the customer wants into measurable characteristics, and then putting these characteristics into functions and design elements. The idea behind DFSS is intuitive and simple. If done well, a company will end up with a product that has what the […]

Three methods used to dissolve a powder in water are compared by the time (in minutes) it takes until the powder is fully dissolved. The results are summarized in the following table: It is thought that the population means of the three methods m1, m2 and m3 are not all equal (i.e., at least one m […]

In Six Sigma work, practitioners normally are expected to conduct a gage R&R study to verify that that the measurement systems being used are providing measurements free from variations due to repeatability and reproducibility problems. This is usually done in the Measure phase of DMAIC (Define, Measure, Analyze, Improve, Control) prior to data analysis so […]

Lean government. The very idea sounds implausible. Even to the seasoned Lean practitioner, the idea of a Lean government sounds far fetched. Governments are traditionally seen as the epitome of bureaucracy, and the guardians of red tape, incomprehensible forms and endless queues. But there are workable Lean strategies for governments seeking to reduce waste and […]

Everyone is taught in school the equation of a straight line: Y = a + bX Where a is the Y-intercept and b is the slope of the line. Using this equation and given any value of X, anyone can compute the corresponding Y. In Figure 1, Y = 3 + 2X. It is easy […]

The power of the test is the measure of how good a hypothesis test is. A “good” test should reject a null hypothesis when it is false and accept it when it is true.

The DMAIC toolkit is excellent for solving technical complexity problems. However, you may have noticed that Lean Six Sigma is not as adept at helping solve people problems. The solution is an integrated DMIAC/change management roadmap.