iSixSigma

data mining

Process Data Mining: Partitioning Variance

Manufacturing facilities can be faced with major challenges when it comes to process improvement, largely because practitioners don’t always know enough about the underlying process factors (x’s) are that drive the improvement metric (Y). Practitioners might have a brainstorming session to tap into the collective experience of experts involved in the process, and design experiments…

Capabilities of Neural Network as Software Model-Builder

One branch of computational intelligence tools, neural networks, is worth surveying as part of the extended data mining and modeling toolkit. The focus here is on a specific kind of neural network applied to empirical model-building – comparing and contrasting its capabilities and performance to more traditional tools like regression analysis. Neural Networks Mimic Biological…

Using Vector Analysis for Turbo-Charged Data Mining

When the occasion requires it, there is often a better, faster path to Six Sigma results. Quality professionals can use the elegant theory that underlies Six Sigma statistical methods to turbo-charge projects. The underlying, unifying concept of turbo-charged Six Sigma is called vector analysis. When columns of measurements are treated as vectors, all of the…

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