METHOD AND SYSTEM FOR CONTROLLING A PRODUCTION SYSTEM TO MANUFACTURE A PRODUCT

A machine learning module (BNN) is provided trained to generate from a design data record (DR) specifying a design variant, a predictive performance distribution (PD) and a constraint compliance distribution (CCD) of the design variant. Furthermore, a variety of design data records (DR) is generated, for each of which the following steps are performed:- A predictive performance distribution (PD) and a constraint compliance distribution (CCD) are generated by the machine learning module (BNN).- The predictive performance distribution (PD) is compared with performance values (PPV) of previously evaluated design data records.- Depending on the constraint compliance distribution (CCD) and the comparison, a simulation (SIM) of the corresponding design variant is either run or skipped.- A design evaluation record (DER) is output which comprises a performance value and constraint compliance data each derived from the simulation if the simulation is run or, otherwise, each derived from the predictive performance distribution (PD) and the constraint compliance distribution (CCD). Depending on the design evaluation records (DER), a performance-optimizing and constraint-compliant design data record (ODR) is selected from the variety of design data records (DR). The selected design data record (ODR) is then output for controlling the production system (PP).