Keywords: Circular economy, Digital thread, Digital twins, Sustainability, Systems engineering
Astract: The perception of the value and propriety of modern engineered systems is changing. In addition to their functional and extra-functional properties, nowadays’ systems are also evaluated by their sustainability properties. The next generation of systems will be characterized by an overall elevated sustainability—including their post-life, driven by efficient value retention mechanisms. Current systems engineering practices fall short of supporting these ambitions and need to be revised appropriately. In this paper, we introduce the concept of circular systems engineering, a novel paradigm for systems sustainability, and define two principles to successfully implement it: end-to-end sustainability and bipartite sustainability. We outline typical organizational evolution patterns that lead to the implementation and adoption of circularity principles, and outline key challenges and research opportunities.

Keywords: Internet of Production, Industry 4.0, Digital Shadow, Digital Twin, Smart Production

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Astract: The COVID-19 pandemic did not only dramatically impact the personal and social lives, for many academics, it also demanded immediate changes to the way their courses are taught. While a pragmatic approach is to do conventional lectures via video streaming platforms, much more may be done to educate students also in a remote setting properly. This particularly holds true for practice-oriented and technology-engaging courses. This paper describes our experience of transforming an in-person Master level class on model-driven software engineering into a distance learning one. We describe the structure, the content, the teaching and examination format, and the used platforms in detail. We critically reflect on our experiences and report the feedback gained by a post-class student evaluation. We believe this paper provides meaningful lessons learned and best practices for other educators challenged with the task of teaching similar courses in a remote setting. With this paper, we publish an openly available Github repository that features all course content including sample solutions for all practical lab assignments.

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Astract: With the emergence of Cyber-Physical Systems (CPS), several sophisticated runtime monitoring solutions havebeen proposed in order to deal with extensive execution logs. One promising development in this respect is the integration oftime series databases that support the storage of massive amounts of historical data as well as to provide fast query capabilitiesto reason about runtime properties of such CPS.In this paper, we discuss how conceptual modeling can benefit from time series databases, and vice versa. In particular,we present how metamodels and their instances, i.e., models, can be partially mapped to time series databases. Thus, thetraceability between design and simulation/runtime activities can be ensured by retrieving and accessing runtime information,i.e., time series data, in design models. On this basis, the contribution of this paper is four-fold. First, a dedicated profilefor annotating design models for time series databases is presented. Second, a mapping for integrating the metamodelingframework EMF with InfluxDB is introduced as a technology backbone enabling two distinct mapping strategies for modelinformation. Third, we demonstrate how continuous time series queries can be combined with the Object Constraint Language(OCL) for navigation through models, now enriched with derived runtime properties. Finally, we also present an initial evaluationof the different mapping strategies with respect to data storage and query performance. Our initial results show the efficiency ofapplying derived runtime properties as time series queries also for large model histories.

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