Data Assets for Decision Support in Multi -Stage Production Systems Industrial Business Process Management using ADOxx

This paper introduces data asset and knowledge management aspects for Industrial Business Process Management (IBPM), positioned a novel research direction for information science (IS). The idea of IBPM has been developed based on the challenges observed in the context of the European Commission GO0D MAN project. Companies in the manufacturing and production industry currently face the challenge to continuously improve their flexibility and efficiency while keeping their high-quality standards. Stakeholders involved in this transformation process face the need to obtain information in real-time across physical and virtual production systems, assess and interpret these streams and take a decision on the results. The environment proposed enables the interpretation of data/information artefacts as input for decision making, therefore empowering human/expert involvement in the digital transformation process. A hybrid conceptual modelling method has been identified, that supports domain experts to a) capture the production system in a semantically rich format, b) design the transformation, c) semantically lift data streams towards data assets and d) enact decision support functionality based on the interpretation of the model artefact. The evaluation of the concept is presented as a proof-of-concept implementation using injection and composition techniques using abstract metamodeling building blocks on the metamodeling platform ADOxx.