Block 5 - lecture 1 Flashcards

1
Q

What does ‘attribute’ refer to?

A

when a quality characteristic comforms or doesn’t conform to specifications (pass/fail)

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2
Q

When are attributes used?

A

measurements are:

  • not possible
  • time consuming
  • costly
  • not needed
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3
Q

When aren’t measurements possible?

A
  • visibly inspected eg. colour, missing parts, damage
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4
Q

Example of quantitative measures being too time consuming?

A

vernier vs go-no-go gauge

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5
Q

nonconformity?

A

part doesn’t meet specification

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6
Q

defect?

A

part doesn’t meet usage requirement

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7
Q

nonconforming unit?

A

an example of the product or service that has a nonconformity

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8
Q

limitations of control charts for variables?

A
  • don’t work when the quality characteristics are attributes

- an Xbar and R chart for each characteristic could be expensive

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9
Q

types of attribute charts for nonconformity?

A
  • p chart

- np chart

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10
Q

p charts?

A

a Proportion chart showing the proportion nonconforming in the subgroup (% or 0.)

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11
Q

np charts?

A

Number of nonconforming

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12
Q

types of attribute charts for nonconformities?

A
  • c chart

- u chart

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13
Q

c chart?

A

count of nonconformities on single units

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14
Q

downside of p charts?

A
  • typically low proportion nonconforming means large subgroups are needed
  • less sensitive to variation than Xbar and R
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15
Q

possible uses of a p chart?

A
  • control a characteristic (like with Xbar and R), a group of characteristics or the entire product
  • determine average quality level
  • show changes in the average
  • show improvements / effectiveness of ideas
  • measure performance of operators and management
  • determine acceptance before shipment to customer
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16
Q

subgroup sizes for np and p?

A

np chart - constant

p chart - variable or constant

17
Q

process for p chart construction?

A
  1. select quality characteristic (eg. single characteristic, part or product)
  2. select subgroup size (>50) use equation with Z from confidence limit
  3. collect data (>25) and calculate proportion nonconforming
  4. calculate trial central line and control limits
  5. discard data with assignable cause and calculate revised central line and control limits