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Abstract. The management of engineering assets within an organization is a challenging task that aims to optimize their performance through efficient decision making. However, the current asset data management systems suffer from poor system interoperability, data integration issues as well as an enormous amount of stored data, thus preventing a seamless flow of information. The aim of this work is to propose a semantic data model for engineering asset management, focusing on the operation and maintenance phase of its life cycle. Ontologies are proposed because they can capture the semantics of data, create a shared vocabulary to describe the knowledge for sharing in the domain and provide reasoning capabilities. This model will gather all the knowledge necessary to assist in the decision making process in order to improve the asset's availability, longevity and quality of operations.

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Abstract. Performance indicators (PIs) are used to monitor and assess production systems. There are thousands of PIs described in standards or in commercial PI collections; however, the PIs implemented in the factories may differ enormously due to use-case-specific requirements. In this work a reference model is proposed to support the process from a generic description to a use case specific PI implementation. There are two exemplary implementations described utilizing data stream processing and database technologies.