• DocumentCode
    1158322
  • Title

    Statistical process control: what you don´t measure can hurt you!

  • Author

    Eickelmann, N. ; Anant, A.

  • Volume
    20
  • Issue
    2
  • fYear
    2003
  • Firstpage
    49
  • Lastpage
    51
  • Abstract
    Statistical control charts are the most commonly used tools to analyze and monitor process variation and stability. Control charts help us isolate nonrandom causes of variation by plotting a measured attribute of the process over time; the upper and lower control limits are empirically derived from the measurements of process variation over time. If a data point falls outside the control limits, we assume that a nonrandom cause of variation is present. It is important that the control limits appropriately reflect the expected behavior of the process being measured. Measuring the number of escaped defects will alert us to problems in the inspection process even though the control charts might not be showing anything abnormal.
  • Keywords
    inspection; production engineering computing; quality control; statistical process control; control chart; defect density measures; inspection; lower control limits; process variation; quality control; statistical process control; upper control limits; Automatic control; Control charts; Inspection; Lab-on-a-chip; Manufacturing automation; Phase measurement; Process control; Size measurement; Software measurement; Time measurement;
  • fLanguage
    English
  • Journal_Title
    Software, IEEE
  • Publisher
    ieee
  • ISSN
    0740-7459
  • Type

    jour

  • DOI
    10.1109/MS.2003.1184166
  • Filename
    1184166