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Minitab xbar r chart8/18/2023 ![]() ![]() In a mixture pattern, the points tend to fall away from the center line and instead fall near the control limits. ![]() Test 8: Eight points in a row more than 1σ from center line (either side) Test 8 detects a mixture pattern. This short Minitab video demonstrates how to complete the XBar-R chart (SPC) example from the 'Lean Six Sigma and Minitab' guide, published by OPEX Resources. Control limits that are too wide are often caused by stratified data, which occur when a systematic source of variation is present within each subgroup. This test detects control limits that are too wide. Test 7: Fifteen points in a row within 1σ of center line (either side) Test 7 detects a pattern of variation that is sometimes mistaken as evidence of good control. Test 6: Four out of five points more than 1σ from center line (same side) Test 6 detects small shifts in the process. Test 5: Two out of three points more than 2σ from the center line (same side) Test 5 detects small shifts in the process. You want the pattern of variation in a process to be random, but a point that fails Test 4 might indicate that the pattern of variation is predictable. Test 4: Fourteen points in a row, alternating up and down Test 4 detects systematic variation. This test looks for a long series of consecutive points that consistently increase in value or decrease in value. Test 3: Six points in a row, all increasing or all decreasing Test 3 detects trends. If small shifts in the process are of interest, you can use Test 2 to supplement Test 1 in order to create a control chart that has greater sensitivity. Test 2: Nine points in a row on the same side of the center line Test 2 identifies shifts in the process centering or variation. Test 1 is universally recognized as necessary for detecting out-of-control situations. Test 1: One point more than 3σ from center line Test 1 identifies subgroups that are unusual compared to other subgroups. Only Tests 1−4 apply to the R chart portion of this control chart. Test 2 detects a possible shift in the process.Įight tests are available with this control chart. For example, Test 1 detects a single out-of-control point. Each of the tests for special causes detects a specific pattern or trend in your data, which reveals a different aspect of process instability. In a mixture pattern, the points tend to fall away from the center line and instead fall near the control limits.Use the tests for special causes to determine which observations you may need to investigate and to identify specific patterns and trends in your data. K points in a row > 1 standard deviation from center line (either side) Test 8 detects a mixture pattern. ![]() K points in a row within 1 standard deviation of center line (either side) Test 7 detects a pattern of variation that is sometimes mistaken as evidence of good control. K out of K+1 points > 1 standard deviation from center line (same side) Test 6 detects small shifts in the process. K out of K+1 points > 2 standard deviations from center line (same side) Test 5 detects small shifts in the process. K points in a row, alternating up and down Test 4 detects systematic variation. K points in a row, all increasing or all decreasing Test 3 detects trends. K points in a row on same side of center line Test 2 identifies shifts in the process centering or variation. 1 point > K standard deviations from center line Test 1 identifies subgroups that are unusual compared to other subgroups. To change the default settings for future sessions of Minitab, choose File > Options > Control Charts and Quality Tools > Tests. ![]()
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