A process oriented approach to automated quality control

To guarantee a constant quality of manufactured products, it is necessary to optimise the process parameters immediately when deviations of the workpiece quality have been observed. Established methods of quality management are only able to register quality deviations (like the statistical process control) or to analyse them offline with the help of experts (like failure mode and effects analysis). The presented approach develops a process oriented automated quality control for manufacturing in two steps: First, a local quality controller stabilises the product quality to reference values in the pace of workpiece production. In order to obtain the control law for the process parameters, a learning approach is applied. In the second step, the information exchange between the local controllers is established parallel to the workpiece flow in order to obtain an optimised global process. As an example, the method is applied to quality control in the turning process.