I'm Bruno Scibilia. I joined the Paris-based Minitab team in 2007 as a Technical Support Specialist, responding to customer queries regarding the installation and use of Minitab Statistical Software and the project management software Quality Companion.

I now lead a number of the Minitab Public Training courses in Paris.

I obtained a Ph.D. in Design of Experiments (DOE), and then worked as a statistical engineer in the semiconductor industry for six years. I also am a certified Six Sigma Black Belt from the American Society for Quality (ASQ).

I was a practitioner of quality improvement...

Design of experiments (DOEs) is a very effective and powerful statistical tool that can help you understand and improve your processes, and design better products.

DOE lets you assess the main effects of a process as well as the interaction effects (the effect of factor A, for example, may be much larger when factor B is set at a specific level, leading to an interaction). In science and in business, we need to perform experiments to identify the factors that have a significant effect. The objective of DOE is to reduce experimental costs—the number of tests—as much as possible while studying as...

Suppose that on your way to a summer holiday resort (a very distant place), your car breaks down. You might just call the roadside assistance and wait for your car to be towed to a repair shop. But suppose that you think you are smarter than that, and you would like to solve the issue by yourself—or at least evaluate the repair cost. Vehicle breakdowns can occur for a large number of reasons.

Intuitively, when facing a complex problem, we tend to test different solutions as soon as they come to our mind. When we understand that one solution will not work, we will then look for the next...

Macros are very useful for automating and processing sequences of repetitive tasks. For example, generating periodic reports (weekly, monthly or quarterly) often becomes a very tedious and time-consuming activity. The graphs and statistical analyses contained in these reports need to be updated regularly and are always the same (although the data change).

Fortunately, these repetitive tasks can easily be automated with the help of some very simple macros.

You do not need to become a macro expert to automate long sequences of tasks. I'm going to present an example of how graphs and statistical...

Multivariate statistics can be used to better understand the structure of large data sets, typically customer-related data.

Suppose you have a large amount of data about your customers (preferences, degree of satisfaction, expectations, dislikes etc…), and a large number of variables you need to analyze.

Your data might seem somewhat chaotic at first, and you might consider the use of many different types of graphs to better understand the overall data structure. But a large number of variables makes it very difficult to obtain the full picture in only a few graphs. At this point, you need to...

Analyzing the Design

In my last post, I discussed how a DOE was chosen to optimize a chemical-mechanical polishing process in the microelectronics industry. This important process improved the plant's final manufacturing yields. We selected an experimental design that let us study the effects of six process parameters in 16 runs.

Now we'll examine the analysis of the DOE results after the actual tests have been performed. Our objective is to minimize the amount of variability (minimize the Std Dev response) to achieve better wafer uniformity. At the same time we would like to minimize cycle...

Choosing the Right Design

I used to work in the manufacturing industry. Some processes were so complex that even a very experienced and competent engineer would not necessarily know how to identify the best settings for the manufacturing equipment.

You could make a guess using a general idea of what should be done regarding the optimal settings, but that was not sufficient. You need very precise indications of the correct process parameters, considering the specificities of the manufacturing equipment.

Or you could guess the best settings, assess the results, and then try to further improve the...