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Intelligent algorithms and learning are the basis for evolving smart cyber-physical production systems (CPPSs) and Industrie 4.0. A smart image detection algorithm shall be added to reduce downtime due to the extended operation of glass bottles in a yogurt producing plant. To support the engineers in doing so, a comprehensive domain-specific language (DSL), DSL4hDNCS, is introduced, enabling rapid analysis, addressing hardware/software architectures and network-related delays and uncertainties. DSL4hDNCS is defined by a metamodel to avoid ambiguity and enriched by aspects, such as safety, calculation power, and network transmission time. DSL4hDNCS is used to compare (re)deployment alternatives using different technologies, such as edge, fog, and cloud to implement the additional smart algorithm. The evaluation of DSL4hDNCS using an acknowledged Industrie 4.0 demonstrator plant as a case study confirmed the benefit for engineers during the redesign.

(Re)deployment of Smart Algorithms in Cyber–Physical Production Systems Using DSL4hDNCS