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Under the context of Industrie 4.0 (I4.0), future production systems provide balanced operations between manufacturing flexibility and efficiency, realized in an autonomous, horizontal, and decentralized item-level production control framework. Structured interoperability via precise formulations on an appropriate degree is crucial to achieve software engineering efficiency in the system life cycle. However, selecting the degree of formalization can be challenging, as it crucially depends on the desired common understanding (semantic degree) between multiple parties. In this paper, we categorize different semantic degrees and map a set of technologies in industrial automation to their associated degrees. Furthermore, we created guidelines to assist engineers selecting appropriate semantic degrees in their design. We applied these guidelines on publicly available scenarios to examine the validity of the approach, and identified semantic elements over internally developed use cases concerning plug-and-produce.

Software architectures and their representations in models are instrumental in achieving sustainability and the fulfillment of requirements. In this context, sustainability encompasses cost efficient maintainability and evolvability, which are central concerns for long living software systems. Hence, it is of great importance to support an architect in addressing these concerns when designing and evolving architectures. However, there is no framework available in which a designed architecture can be evaluated against these important quality attributes. In this paper, we address this challenge by proposing seven metrics which characterize the completeness, consistency, correctness and clarity of the documentation. These seven metrics should enable an architect to efficiently identify issues in an architecture model.

For distributed computing, orchestrations along predefined communication paths are used to obtain agreement between system components on the next chosen transition. Although the communication overhead can be high, it can be efficiently reduced by the introduction of knowledge, which provides each local component imperfect view on the global state during run-time. In this paper, given a safety criterion, we formulate the problem how to automatically orchestrate components in a system using stateless precedences between actions under the assist of statically computed knowledge. If the system is diagnosed as unsafe, the use of knowledge can be integrated in the synthesis process to enlarge the set of legal fixing candidates. These new solution candidates may disrespect predefined communication paths but their defined priorities are still guaranteed to be deployable.