![]() This chart is appropriate if you have no natural subgrouping in your data. Select Analyze > Quality and Process > Control Chart Builder.Īn Individual and Moving Range chart of Length appears. ![]() Select Help > Sample Data Folder and open Quality Control/Line Length.jmp.Ģ. If it is, we can use the control limits created by JMP as our baseline or historical limits.ġ. Create the Baseline Control Chartįirst, examine whether the existing process is in control. You want to know: Is this process in control (stable)? Are we getting consistent print quality? What happens when we make improvements to the printing process? Does quality improve? To answer these questions, we need to create control charts and use control limits. The line lengths are measured on a specified page in the middle of each book. For every print run, the first and last books are taken for measurement. Any shorter and there would be a lot of wasted space on the page. ![]() Any longer and the sentence might run off of the page. A line is considered good if it has a printed length of 16 cm +/- 0.2 cm. In this example, we will consider the length of the line. Variations can cause distortion in the line, including skew, thickness, and length problems. In this example, consider a company’s printing process. ![]() Then, to apply these control limits to new data, you would either Specify Control Limits or Specify Multiple Sets of Control Limits (for phase data). In most cases, you would start with Create the Baseline Control Chart, where you let JMP calculate the control limits for you. This example uses Control Chart Builder in three stages. ![]()
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