Using Bootstrap Forests for Semiconductor Yield Analysis in JMP Pro.

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JMP Pro provides many ways to quickly and easily build statistical models that can usefully link inputs to outputs for prediction or explanation. Tree-based methods are a major subset of these, and have many desirable properties that make them both flexible and powerful.

In view of the complexity of the process, high data availability and high-value products, semiconductor manufacturing has always been the benchmark for innovative engineering data analysis. By filling out the form below, you can download a white paper that shows how STMicroelectronics routinely uses bootstrap forests in JMP Pro to tackle difficult engineering problems.

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The paper contains a summary of commonly used analytical approaches, then descriptions of two cases that show the utility of bootstrap forests, one of three options within the Partition platform in JMP Pro.

Even if you are not in the semiconductor industry, if you are interested in how JMP Pro can help you quickly and easily build useful statistical models, you will find this paper valuable.

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