Complexity Space Modelling for Industrial Manufacturing Systems

Abstract

The static and dynamic complexity of an industrial engineered system are integrated in a complexity space modelling approach, where information complexity boundaries expand over time and serve as an indicator for system instability in a static complexity space. In a first step, model-based static and dynamic conceptions of complexity are introduced and described. The necessary capabilities are theoretically demonstrated, alongside a set of assumptions concerning the behavior of industrial system complexity and its functions as a core foundation for the proposed complexity space model. In a second step, the successful application of the proposed modelling approach on a real-world industrial system is presented. Case study results are briefly presented and discussed as a first proof of concept for the general applicability of the proposed modelling approach for current and future industrial systems. In a final step a short research outlook is provided.