22 2 22 2 222 50% -1 -2 -3 +1 +2 +3 0 .6826 1 .9973 3 .9546 2 z value = distance from the center measured in standard deviations Zones A B C C B A
33 3 33 3 333 The process creating the data on the control chart is operating under statistical control Produces a graphic that will have a high center, and sloping sides The points tend to cluster around the center of the chart, show random variation, with only a few points spreading out toward the control limits Points look random ◦ Here is an example of a process running in statistical control:
55 5 55 5 555 Data that fluctuates excessively and fails to center itself around the centerline is characteristic of assignable or non-normal variation Several of these patterns have been classified The next few pages describe the most common patterns seen in processes Not necessarily a bad thing ◦ Heading in right direction ◦ Result of improvement
66 6 66 6 666 A random part located outside of the control limits (1 point outside of zone A) Occurs for a number of reasons Any reason requires investigation before continuing to run the job Reasons to occur: ◦ An incorrect machine adjustment that is immediately noticed and fixed ◦ Errors in measurement or plotting ◦ A cutting tool that “caught a chip” ◦ May be normal variation
88 8 88 8 888 Set of seven or more consecutive points that are all on one side of the center line indicating the center has changed (7 points in zone C or beyond, all on one side of the center line) Usually temporary / sudden A sudden shift in the level of parts shown on a chart can be good or bad ◦ Good: if the shift is bringing the parts back to split limit ◦ Bad; if the shift is taking the parts away from split limit. Reasons to occur: ◦ A change of material ◦ New operator or inspector ◦ An offset change ◦ Two or more machines/suppliers on one chart
10 Trends can also form in the output of a product Defined as consecutive points on a control chart that are steadily increasing or decreasing in value. (7 consecutive points that either increase or decrease in value – also, 10 out of 11 consecutive points that either increase or decrease in value ) Usually gradual Trends can be caused by: ◦ Air, coolant, or part temperatures that are steadily increasing or decreasing ◦ Tool wear that allows a part to steadily increase or decrease in size ◦ A fixture that is constantly wearing, causing the parts to steadily increase or decrease in size ◦ Operator fatigue
12 There are no number rules to identify cycles Cycles are defined as repeated patterns in a process Cycles can be caused by: ◦ Machines that are continually heating up and cooling down ◦ Air temperatures in the shop that rise to a certain point, then are reduced quickly as cooling systems are activated ◦ Tool wear that allows a part to increase or decrease in size until an offset is made ◦ Seasonal
14 Occurs when the points occur in clusters Can be done visually Can be done statistically (2 of 3 points in zone A or beyond – 4 of 5 points in zone B or beyond) Can be caused by: ◦ Differences in setups ◦ Tools moving ◦ Method problems
16 Can be identified by looking for a majority of parts falling very close to the control limits, with very few in the center of the chart (5 or more consecutive points outside zone C) Will have a "sawtooth" look to it Typically, this type of situation is actually a combination of two separate distributions within a process, one at high limit, and one at low limit Can be caused by: ◦ Two different gages being used ◦ Output from two or more machines mixed together on the same chart
17 Can be identified by looking for erratic ups and downs, but not near the center line (5 or more consecutive points oiutside zone C) Similar to stratification Will have a "sawtooth" look to it Can be caused by: ◦ Gaging concerns (rule of 10s) ◦ Honest reporting?
18 Can be identified by looking for a majority of parts hugging the center line (14 or more consecutive points inside zone C) Will have a "sawtooth" look to it Can be caused by: ◦ Gaging concerns (rule of 10s) ◦ Honest reporting?