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Statistical process control
- Takes periodic samples from process
- Plots samples on control chart
- Determine if its within the limits
- Correct process before defects are produced
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Attribute data
product characteristics that have discrete choice color feel taste
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Variable data
- Product characteristics that can be measured
- Length, size, weight
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Control charts
used to monitor the quality of manufacturing process
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"in control"
- There are no sample points outside control limits
- Most points are near the process center line, without too many close to the control limits
- Approximately equal numbers of sample points occur above and below the center line
- The points appear to be randomly distributed around the center line
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P chart
- Calculate percent defectives in a sample
- based on binomial distribution
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C chart
- count number of defects in an item
- based on poisson distribution
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Mean chart (X-bar Chart)
Measure the central tendency of a sample
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Range chart (R chart)
- The difference between the highest and lowest value
- measure the amount of dispersion in a sample
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Central Limit Theorem
if you graph the means of a series of observations, the data will approach a normal distribution
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Process Capability
- Can it meet design specifications
- Natural variability in a process
- 3 sigma quality - specifications equal to the process control limits
- 6 sigma quality - specifications are twice as large as the control limits
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Cp
- Process capability ratio
- Tolerance range / process range
- Cp<1 not capable
- Cp = 1 just capable
- Cp > 1 process is capable
- Cp = 2 six sigma quality
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Cpk
- Measures if process is off center
- Process capability index
- Cpk = Cp, the process is exactly on center
- Cpk < 0, process is completely outside the design specs
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