Pattern-Based Semantic Composition of Optimal Process Service Plans with ODERU

Luca Mazzola, Patrick Kapahnke, Matthias Klusch

In: Information Integration and Web-based Applications and Services. International Conference on Information Integration and Web-based Applications & Services (iiWAS-17) 19th ACM International Conference on Information Integration and Web-based Applications and Services Salzburg Austria ACM 2017.


To keep pace with the needs of the manufacturing industry of the future, companies need to flexibly react to changing demands and be able to manage production capacities in a rapid and efficient way. This requires agile collaboration among supply chain partners in context of Service-Oriented Architectures (SOA). To this end, we propose a novel pragmatic approach for automatically implementing service-based manufacturing processes at design and runtime, called ODERU. Relying on a set of semantic annotations of business process models encoded into an extension of the BPMN 2.0 standard, it combines pattern-based semantic composition of process service plans and optimization of non-functional aspects by means of QoS-based constraint optimization problem (COP) solving. The ODERU tool is part of a platform for cloud-based elastic manufacturing. In this paper we present the foundations of ODERU, showcasing its application to two manufacturing processes with conflicting requirements showing how it solves the problem by leveraging the Everything-as-a-Service (XaaS) approach.


German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz