Block 4 - lecture 4 Flashcards

1
Q

aspects of charts for variable subgroup size?

A
  • different control limits
  • higher n value narrows the limits
  • difficult to interpret
    SHOULD BE AVOIDED
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2
Q

centreline of charts for trends?

A

equation of centreline can be calculated using:
Xbar = a + bG

(equations for a and b in bklet, make a table with G, Xbar, GXbar and G^2)

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3
Q

control limits for charts for trends?

A

A2 Rbar or A sigma subscript 0 either side of the centerline.

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4
Q

charts for moving average?

A

average is taken of the previous n number of samples

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5
Q

charts for moving range?

A

range is taken of the previous n number of samples

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6
Q

Charts for median and range?

A

data is collected in subgroups like Xbar and R, but instead of a mean a median (Md) is taken.

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7
Q

How to find the centerline of median and range charts?

A

find the median of the medians of the subgroups (Md subscript Md) and the median of the ranges (R subscript Md)

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8
Q

How to find the control limits of median and range charts?

A

use specific equations in bklet

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9
Q

advantages of charts for median and range?

A
  • less arithmetic
  • easy understanding
  • easily maintained by operators`
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10
Q

disadvantages of charts for median and range?

A

doesn’t take extreme values into account

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11
Q

reasons only one measurement might be made in a sample?

A
  • too expensive
  • too time consuming
  • destructive
  • very few samples
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12
Q

working out the range for charts for individual values?

A

find the range from the last point ie.2nd-1st

this is plotted between the subgroup numbers

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13
Q

advantages of X chart?

A
  • no calculations
  • easy to do on shop floor
  • direct comparison to specs
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14
Q

disadvantages of X chart?

A
  • requires a lot of subgroups to show out of control condition
  • doesn’t summarize the data as well as Xbar
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15
Q

Non-conformance limits?

A

a limit for Xbar, like specs are to individual values

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16
Q

exponential weighted (geometric) moving average?

A

moving average that gives more weight to more recent values

17
Q

advantage of exponential weighted (geometric) moving average?

A
  • can detect small shifts in the process faster than regular running averages
18
Q

disadvantage of exponential weighted (geometric) moving average?

A
  • doesn’t react as quickly as the X bar chart
19
Q

weighting of current subgroup (lambda)?

A

between 0.05 and 0.25

smaller values detect change faster