Enablers for Self-optimizing Production Systems in the Context of Industrie 4.0

In an environment that is shaped by global competition and individualization, manufacturers in high-wage countries are increasingly forced to optimize their production in order to compensate for their high labor costs. Within the Cluster of Excellence “Integrative Production Technology for High-Wage Countries” at the RWTH Aachen University, this problem is addressed in an attempt to find solutions for the recovery of the competitive edge for manufacturing in high-wage countries. As an identified core mechanism of the resulting theory of production, self-optimizing production systems offer the potential of greatly enhancing the productivity and flexibility in manufacturing by integrating self-optimizing functions along the whole production process. However, as of today their implementation into an industrial environment is still hindered by the lack of present preconditions. Therefore, this paper focuses on the establishment and demonstration of enablers for self-optimizing production systems. Within the first part of this work, the conceptual background and a definition for self-optimizing production systems are introduced. The former is focused on the process of self-optimization as well as on its potential benefits. Subsequently, the four main enablers are identified: Flexibility, variability, cognition and autonomy. Those are analyzed with regards to their individual function and possible implementation. At the end, the implementation is demonstrated along two project examples. Firstly, it is shown how the concept of a self-organizing material flow system can be further improved with the developed theory. Finally, the concept is applied to the self-optimizing production of small laser systems.