By Jack Reece
For a producing job to stay aggressive, engineers needs to conscientiously follow facts methodologies that permit them to appreciate the assets and outcomes of out of control technique version. during this example-rich textual content, writer Jack Reece explains easy comparative facts and demonstrates the way to use JMP to ascertain uncooked info graphically and to generate regression types related to fastened and random results. the subsequent significant themes are addressed:
- Characterizing the dimension technique
- Analyzing procedure functionality
- Developing applicable keep watch over mechanisms for tracking size and function
even though a number of the examples depend upon case reviews, principally within the semiconductor production sector, the foundations defined and the tools used follow typically to the examine of any strategy or production job. This booklet assumes that the reader has a few wisdom of JMP software program, yet doesn't imagine wide statistical knowledge.
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For a producing job to stay aggressive, engineers needs to conscientiously observe information methodologies that permit them to appreciate the resources and outcomes of out of control method version. during this example-rich textual content, writer Jack Reece explains basic comparative information and demonstrates easy methods to use JMP to ascertain uncooked information graphically and to generate regression versions regarding fastened and random results.
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Additional info for Measurement, Analysis, and Control Using Jmp: Quality Techniques for Manufacturing
25 shows the completed formula. 25 The Completed Formula The formula for the upper 95% CI boundary for the mean is identical to that just described except for the value entered for p. 975, which reflects the area under the student’s t distribution left of that upper boundary. 95. 20, data columns six and seven, respectively, provide the upper and lower 95% CI bounds for the standard deviation. 8 provides these values based on the varying sample sizes. 05 for a 95% confidence interval). The reader can display the formulas associated with data columns six and seven to see the actual JMP implementation.
19 in order to produce a plot showing how the other two parameters (Sample Size and Power) vary under set conditions of Alpha risk and Difference to detect, given an expected Error Std Dev. 19 Plots of Power versus Sample Size, Given Alpha and a Difference to Detect Relative to Error Chapter 1: Basic Concepts of Measurement Capability 21 Uncertainty in Estimating Means and Standard Deviations Anyone who has had a basic course in statistical process control (SPC) or perhaps in some level of measurement capability instruction might have been struck by the large numbers of observations usually recommended.
Again this type of study estimates standard deviations or variances, so an investigator planning this investigation must pay particular attention to generating enough data such that each measurement factor has enough degrees of freedom (replicates) associated with it to produce a reliable estimate. Therefore, a complete and robust measurement study to estimate total measurement error and to separate repeatability and reproducibility errors can require weeks to complete. This is not to say that the measurement study should dominate the work of individuals running a process.
Measurement, Analysis, and Control Using Jmp: Quality Techniques for Manufacturing by Jack Reece