Basics of Control Chart in Pharmaceutical Industry

Control Charts is a statistical tool to determine if a process is in control.

Types of Control Charts

  • Variable Control Charts
  • Attribute Control Charts

Variable Control Charts

Deal with items that can be measured. For examples:
1) Weight
2) Height
3) Speed
4) Volume

Types of Variable Control Charts

  • X-Bar chart: deals with a average value in a process.
  • R chart: takes into count the range of the values.
  • MA chart: take into count the moving average of a process.

Attribute Control Charts

Control charts that factor in the quality attributes of a process to determine if the process is performing in or out of control.

Types of Attribute Control Charts

  • P Chart: a chart of the percent defective in each sample set.
  • C chart: a chart of the number of defects per unit in each sample set.
  • U chart: a chart of the average number of defects in each sample set.

Reasons for Using Control Charts in Pharma Industry

  • Improve productivity
  • Make defects visible
  • Determine what process adjustments need to be made
  • Determine if process is “in” or “out of control

Control Chart Key Terms

  • Out of Control: the process may not performing correctly
  • In Control: the process may be performing correctly
  • UCL: upper control limit
  • LCL: lower control limit
  • Average value

Process is OUT of control if:

  • One or multiple points outside the control limits
  • Eight points in a row above the average value
  • Multiple points in a row near the control limits

Process is IN control if:

  • The sample points fall between the control limits
  • There are no major trends forming, i.e.. The points vary, both above and below the average value.

Calculating Major Lines in a Control Chart

  • Average Value: take the average of the sample data
  • UCL: Multiply the Standard deviation by three. Then add that value to the Average Value.
  • LCL: Multiply the Standard deviation by three. Then subtract that value from the Average Value.


  • First Step: Determine what type of data you are working with.
  • Second Step: Determine what type of control chart to use with your data set.
  • Third Step: Calculate the average and the control limits.

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