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The paper describes an analytical method to identify problem tools in a manufacturing environment. Using JMP software, one visualized a yield problem, collected a relevant data set, and created a Standard Least Squares model to identify the tools contributing most to the problem. Once identified, further analysis in JMP software gave insight into the underlying root cause that allowed one to fix the problem and prevent future occurrences. On numerous occasions, one has found this method to be an effective and efficient method to identify problem tools.
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