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Showing posts with the label Yield

Process Control and Capability

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  Process Stability Vs Capability Stability means a process is behaving in a predictable way but it doesn't necessarily mean it meets the customer expectations.  Process capability measures to what extent it is able to satisfy the customer requirements. The first step for process improvement is to achieve stability. We analyse this with Statistical Process Control . As a result of this analysis we may find out-of-control situations due to special causes. In this case we need to resolve these causes to make the process stable.  Once the process is stable, we can find out to what extent is it able to meet customer expectations. This is done by measuring   Process Capability . Descriptive Statistics with Excel Download a copy of Excel file   Capability.xlsx   from OneDrive on to your PC to run it. In sheet Diameter  in column A we have 500 measurements of a critical diameter. After being confident that our process is stable we can character...

Response Surface Design Of Experiments with Excel

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Design of Experiments is a useful methodology for process improvement. The purpose is to find a relationship between process variables we can control, and key process outputs, to increase process capability . You can use Excel statistical analysis tools, Solver, Pivot charts, etc. to plan and analyse the results of these experiments. The first approach is to look for a linear relationship, as shown in:   Excel DOE But in some cases this relationship may not be linear, in which case we will try a quadratic model with Response Surface DOE . We will use an example in this Excel file you can download: Download file   ExcelResponseSurface.xlsm   from OneDrive to your PC. In this example we are trying to maximize process yield, acting on the critical factors pH , Temperature and Time . We will run the experiments in the Experiments simulation sheet using coded values.   Code pH Temperature Time -1 2 120 7 1 12 150 15 Factorial Experiments We start by running...