Circular systems engineering

IF 2 3区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Software and Systems Modeling Pub Date : 2024-02-29 DOI:10.1007/s10270-024-01154-4
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Abstract

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.

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循环系统工程
摘要 人们对现代工程系统的价值和适当性的认识正在发生变化。除了功能和功能外特性外,如今人们还根据系统的可持续性特性对其进行评估。在高效保值机制的驱动下,下一代系统的特点将是整体可持续性的提升,包括其使用寿命的延长。当前的系统工程实践无法支持这些雄心壮志,因此需要进行适当修改。在本文中,我们介绍了循环系统工程的概念--一种新的系统可持续性范式,并定义了成功实施这一范式的两个原则:端到端可持续性和双向可持续性。我们概述了导致实施和采用循环性原则的典型组织演变模式,并概述了主要挑战和研究机会。
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来源期刊
Software and Systems Modeling
Software and Systems Modeling 工程技术-计算机:软件工程
CiteScore
6.00
自引率
20.00%
发文量
104
审稿时长
>12 weeks
期刊介绍: We invite authors to submit papers that discuss and analyze research challenges and experiences pertaining to software and system modeling languages, techniques, tools, practices and other facets. The following are some of the topic areas that are of special interest, but the journal publishes on a wide range of software and systems modeling concerns: Domain-specific models and modeling standards; Model-based testing techniques; Model-based simulation techniques; Formal syntax and semantics of modeling languages such as the UML; Rigorous model-based analysis; Model composition, refinement and transformation; Software Language Engineering; Modeling Languages in Science and Engineering; Language Adaptation and Composition; Metamodeling techniques; Measuring quality of models and languages; Ontological approaches to model engineering; Generating test and code artifacts from models; Model synthesis; Methodology; Model development tool environments; Modeling Cyberphysical Systems; Data intensive modeling; Derivation of explicit models from data; Case studies and experience reports with significant modeling lessons learned; Comparative analyses of modeling languages and techniques; Scientific assessment of modeling practices
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