Plastics processing companies can only meet up to present‐day quality requirements if they adopt systematic methods. This holds particularly true for the extremely stringent demands that are now placed on injection molding technology. Working on from a sound experimental basis, it is possible to define cause/effect correlations for two sets of empirical data (the current process conditions and the molded part attributes) for each quality variable by using a statistical process model. The process model enables the processor to calculate the effect of each individual combination of parameters in the experimental area and to perform an optimization. If it proves possible to describe the cause/effect correlation between the fluctuations in the molded part attributes and those in the process parameters by means of a statistical process model, then this can be used for the continuous monitoring of production. The statistical experimentation method and continuous process monitoring are grouped together to form the so‐called CPC concept, permitting traceable, gap‐free documentation of the quality data for a production chain. Three examples are set out to illustrate the possibilities for use of the CPC concept; these are then assessed on the basis of the benefit observed.
