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Elements and Applications of a Control Chart

Each Control Chart actually consists of two graphs, an upper and a lower, which are described below under plotting areas. A Control Chart is made up of ten elements.

  1. Title. The title briefly describes the information which is displayed.
  2. Legend. This is information on how and when the data were collected.
  3. Data Collection Section. The counts or measurements are recorded in the data collection section of the Control Chart prior to being graphed.
  4. Plotting Areas. A Control Chart has two areas—an upper graph and a lower graph—where the data is plotted.
  5. The upper graph plots either the individual values, in the case of an Individual X and Moving Range chart, or the average (mean value) of the sample or subgroup in the case of an X-Bar and R chart.
  6. The lower graph plots the moving range for Individual X and Moving Range charts, or the range of values found in the subgroups for X-Bar and R charts.
  7. Vertical or Y-Axis. This axis reflects the magnitude of the data collected. The Y-axis shows the scale of the measurement for variables data, or the count (frequency) or percentage of occurrence of an event for attribute data.
  8. Horizontal or X-Axis. This axis displays the chronological order in which the data were collected.
  9. Control Limits. Control limits are set at a distance of 3 sigma above and 3 sigma below the centerline. They indicate variation from the centerline and are calculated by using the actual values plotted on the Control Chart graphs.
  10. Centerline. This line is drawn at the average or mean value of all the plotted data. The upper and lower graphs each have a separate centerline.

 

Application of Control Charts

  • The control chart, though originally developed for quality control in manufacturing, is applicable to all sorts of repetitive activities in any kind of organization.
  • They can be used for services as well as products, for people, machines, cost, and so on. For example, we can plot errors on engineering drawings, errors on plans and documents, and errors in computer software as c or u charts.
  • Sometimes, the quality control engineer has a choice between variable control charts and attribute control charts.

Advantages of attribute control charts

  • Allowing for quick summaries, that is, the engineer may simply classify products as acceptable or unacceptable, based on various quality criteria.
  • Thus, attribute charts sometimes bypass the need for expensive, precise devices and timeconsuming measurement procedures. More easily understood by managers unfamiliar with quality control procedures.

Advantages of variable control charts

  • More sensitive than attribute control charts.
  • Therefore, variable control charts may alert us to quality problems before any actual “unacceptables” (as detected by the attribute chart) will occur.
  • Montgomery (1985) calls the variable control charts leading indicators of trouble that will sound an alarm before the number of rejects (scrap) increases in the production process.
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