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Quality Control charts

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Quality Control charts Statistics can be gathered by collecting information from the entire collection of values or only a portion Population a collection of all ... – PowerPoint PPT presentation

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Title: Quality Control charts


1
Quality Control charts
2
Population vs Samples
  • Statistics can be gathered by collecting
    information from the entire collection of values
    or only a portion
  • Population a collection of all possible
    elements, values, etc associated with the
    situation
  • Deductive or descriptive
  • Sample a subset of elements or measurements
    taken from a populations
  • Inductive
  • Quality control relies on inductive statistics

3
Sampling
  • Store orders 1000 shirts
  • 200 blue, 800 white
  • Should the manager check all?
  • Easier way collect samples of 10 at random and
    check how many are blue

4
Types of data
  • Variable data
  • Measured characteristics
  • Tend to be continuous
  • Attribute data
  • Observable characteristics
  • Tend to be discrete
  • Data can be grouped or ungrouped

5
Accuracy, Precision, Error
  • Accuracy how far from actual value
  • Precision ability to repeat the same
    measurement and get the same value
  • Error how far a measured value is from the true
    value

6
Accuracy, Precision, Error
7
Data representation
  • Histograms and frequency diagrams are similar
  • They show distribution
  • Data are grouped into cells
  • Find range and interval.

8
Data analysis
  • Central tendency
  • Mean
  • For population
  • Average
  • When data is from a sample

9
Data analysis
  • Range
  • R Xmax Xmin
  • Standard deviation
  • Shows dispersion of data within the distribution
  • Population
  • Sample

10
Variable control charts
  • Decision making tools
  • Determine out-of-control condition
  • Process capability
  • Problem solving tools
  • Locate/identify cause for poor quality
  • Monitor production

11
Control charts
  • Samples are taken
  • Averages of the subgroups plotted
  • Centerline of the chart is the central tendency
    (mean or average)
  • Chart has upper (UCL) and low (LCL) control
    limits
  • They represent /-3?

12
Control charts
13
and R charts
  • Monitor subgroup averages from sampled data
  • R monitors deviation from average range
  • Choose sample size
  • Determine average of the subgroups
  • Compute UCL and LCL
  • Plot data
  • If falls within the limits, accept population
    else investigate or reject

14
and R charts
  • For chart
  • UCL 3?
  • LCL - 3?
  • If the sample size of the subgroup is between 4
    and 10, the distribution is nearly normal
  • Shewart developed an approximation for 3? for
    small subgroup sizes (lt20)

15
and R charts
  • UCL A2
  • LCL A2
  • A2 ? 3 ?
  • Centerline is

16
and R charts
  • The R chart is to show the variation of the
    ranges within the subgroups
  • For R chart
  • UCL 3?R
  • LCL - 3?R
  • Centerline is
  • For small subgroup sample sizes
  • UCL D4
  • LCL D3

17
Control charts for attributes
  • Attributes are characteristics associated with a
    product or service and are not easily measurable
  • Used when measurements may not be possible

18
Control charts for attributes
  • Advantages
  • Relatively easy
  • Inexpensive
  • Easy to use for service type OS
  • Disadvantages
  • Does not provide reason for non-conformity
  • Do not provide detailed information

19
Control charts for attributes
  • p charts
  • Binomial distribution
  • Fraction of non-conforming parts, p
  • Constant sample size, n
  • Collect data
  • Track number of non conforming parts, np

20
Control charts for attributes
  • p charts
  • Compute the mean fraction of non-conforming parts
    for all the samples, which is the centerline for
    the chart,
  • UCL and LCL

21
Control charts for attributes
  • c charts
  • number of non-conforming parts, c
  • Used when non-conformities are scattered through
    a continuous flow of product inclusions or cracks
    on sheet metal surface
  • Specify what is to be inspected
  • eg. Number of cracks per 3 square feet.

22
Control charts for attributes
  • c charts
  • Calculate centerline
  • UCL and LCL
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