Many people use Microsoft Excel on a daily basis. Yet few people realize the extent of Excel's analytical capabilities. Fewer still put these capabilities to work for process improvement, product improvement and profit.Most Excel users are aware of the common formulas and charts. But with some creativity, users can produce tools like control charts, Pareto charts and box-and-whisker plots (see "Using Excel for Data Analysis," Quality Digest, October 1997). And with a little guidance, users can employ more advanced statistical methods with Excel. This article presents a how-to approach for one such advanced technique-Weibull analysis.
You haven't turned the page yet? Those of you who remain probably fall under one of two categories: those familiar with reliability data analysis, and Excel enthusiasts who are curious to learn one more way to exploit this versatile software. I predict readers in both groups will be glad they stuck around.
For the uninitiated, Weibull analysis is a method for modeling data sets containing values greater than zero, such as failure data. Weibull analysis can make predictions about a product's life, compare the reliability of competing product designs, statistically establish warranty policies or proactively manage spare parts inventories, to name just a few common industrial applications. In academia, Weibull analysis has modeled such diverse phenomena as the length of labor strikes, AIDS mortality and earthquake probabilities.
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