11 1 11 1 111. 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.

Presentation on theme: "11 1 11 1 111. 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."— Presentation transcript:

11 1 11 1 111

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:

44 4 44 4 444

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

77 7 77 7 777

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

99 9 99 9 999

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

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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

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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

15 Grouping.7510.7490.7495..7505.7500

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?

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20  Let’s finish the exercise on pg. 594/602

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