Algorithm 2: Controller

INPUT: Quality threshold for the quality goal (surface quality, weight, or dimensions), integer n for the minimum shot distance between the controller actions, and the reference function f as described in Algorithm 1. OUTPUT: No output, the algorithm runs perpetually. WHILE forever DO |  Part Production |  |_   A new part is produced |  Quality Measurement |  |   The surface quality smeasured is inspected using CNN. |  |   The weight wmeasured is measured using the scale. |  |_  The dimensions dmeasured are measured using the cylindrical dimension |     measurement system. |  Quality Prediction |   |   Let M be the vector of current machine parameters, r the running time of |   |   the machine, E the vector of current ambient sensor data, and A the vector |   |   of current analog sensor data. |   |   The surface quality spred is predicted by R1(M, r, E, A). |   |   The weight wpred is predicted by R2(M, r, E, A). |   |_  The dimensions dpred are predicted by R3(M, r, E, A). |  Quality Control |   |   IF the measured quality value is outside of the given threshold THEN |   |  | IF there has been a machine parameters update within the last n shots THEN |   |  | |_ Terminate this loop |   |  |IF the measured quality deviates strongly from the predicted quality THEN |   |  | |_ Warn the user: an external factor might influence the part quality. |   |  |_Use Algorithm 1 to calculate the new machine parameters based on M, |   |    r, E, and f. |_    |_   |_Set the new machine parameters.