Although Life Cycle Sustainability Assessments (LCSA) are important in evaluating the sustainability of complex products and services, there is no sufficient support for engineers performing LCSA. The concept of an Engineering Graph focuses on the relations of data within engineering. It provides a model that leverages existing data in engineering and extendibility to include specialized databases and open and public data from the semantic web. This paper proposes a concept of how Engineering Graphs can be used to address the issues of LCSA and support engineers.
Produkt- und Betriebsdaten können durch den Einsatz von Künstlicher Intelligenz (KI) genutzt werden, um die Produktentwicklung zu verbessern. Voraussetzung dafür ist, dass Daten in der richtigen Qualität und in ausreichender Anzahl verfügbar sind. Um diese Voraussetzung (KI-Readiness) besser zu erfüllen, benötigt es häufig großer Anstrengungen im Unternehmen. Prozesse, Methoden und IT-Systeme müssen global harmonisiert werden. In diesem Beitrag werden die Evolutionsschritte hin zur „KI-Readiness“ in der Produktentwicklung beschrieben.
The requirements space is increasing due to non-functional areas such as security, resilience and sustainability gaining in importance. This creates a complex and dynamic space which makes it hard for engineers to take good data driven design decisions. Increasing the quality of design decisions allows to better set up development projects and develop more successful products and services. The design can most heavily be influenced in the early design phases, where design flexibility is high and resource commitment is low. Unfortunately, the system knowledge is also low in early phases. The Engineering Graph is a concept that connects data from different internal and external sources. It allows to connect product data stored in Product Lifecycle Management systems with system models and also add external sources from the Wikimedia Knowledge Graph, World Health Organization and World Bank. This interconnected data allows the support of engineers in managing the complex and dynamic requirement space and provide high system knowledge in the early design phases to support design decisions.
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