AMS*SPC - Statistical process control

One of the most popular methods for the improvement of production processes is the statistical process control. However the expression statistical process control is actually not a correct description. The term statistical process regulation would be more applicable to the task situation. SPC helps recognize and evaluate the dispersion of processes significantly contributing to reducing rejects, rework and defective products.

Using statistical methods (in this case in particular sampling technique and normal distribution) product parameters that are relevant for the quality are evaluated and analysed (as a result of the production process steps, e.g. surface hardness).

By comparing these analysis results, it is possible to evaluate if a treatment process' parameters need to be adjusted and to which extend. This form of data evaluation, control and subsequent improvement of the process is colloquially called SPC (statistical process control; while "control" can be understood as "directing" or "regulating").

The statistical process control aims at tracking the essential test criteria following a process. This way deviations can be recognized at an early state and appropriate correction measures can be made or the client is consulted before faulty products occur. Another declared aim is to check if the plants are suitable for complying with the required tolerances before their commissioning.

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Functional sequence

The only practical way to perform a control chart analysis in AMS is to use „comparable" positions and processes.

Selecting positions

Via suitable search criteria - inspired by those of the detailed order search - a selection of comparable and evaluable positions is enabled.

These criteria are:

  • plants and
  • program / heat treatment process and
  • period
  • number of positions to be considered and
  • serial position or optionally
  • customer and component features (e.g. component name, drawing number, component ID)

Positions and individual tests of positions can be selected and deselected by the user individually. Numerous test characteristics are provided and can be analysed.

Setting the control parameters

The following rules of conduct / parameters can be set for the control chart:

  • UTL = upper tolerance limit (determined through the customer's target settings)
  • UIL = upper intervention limit (determinable individually)
  • LIL = lower intervention limit (determinable individually)
  • LTL = lower intervention limit (determined through the customer's target settings)
  • free commentary

SPC Auswertung - Klicken zum Vergrößern

Creation of a SPC-control chart

The control chart is inspired by recognized and approved layouts. However individual customer requests can be implemented.

The control chart gives information on:

  • standard deviation sq. or variance. Calculation is made according to known formulas.

    SPC Varianz - Klicken zum Vergrößern

  • cp and cpk value as measurement of the process capability, calculated according to known formulas. The quality capability thereby is considered under real process conditions. The effect of process improvement in the long-term trend becomes evident. Therefore an observation period with the corresponding observational horizon should be chosen. The quality capability under real process conditions is identified (requires CpK>1,33= ,4s)
  • Cp  Cpk
    Formel CP - Klicken zum Vergrößern Formel CPk - Klicken zum Vergrößern