1. Introduction
Ever shorter innovation cycles, the increasing amount of product functionality and a customisation of products lead to rising complexity of production control of current production systems. However, established production control systems can only respond to familiar situations, such as certain disturbances, with a given behaviour. For this reason, the production control cannot respond adequately to unforeseen changes (e.g. cancellation of jobs) in the production process. They are not sufficiently capable of learning and accordingly only partially able to compensate disturbances in the production process or to ensure the correct dispatching of rush jobs. One solution approach to handle these challenges is the paradigm of self-optimisation. Self-optimisation describes the ability of a technical system to endogenously adapt its objective regarding changing influences and thus adapt the system’s behaviour in accordance with the objectives. Behaviour adaptation may be performed by changing the parameters or the structure of the system. In terms of a self-optimising production control, possible objectives are “maximising the output”, “minimising the energy consumption” and “maximising the delivery reliability”.