Exploring indicators of system-of-systems resilience: outcomes of a health systems design workshop at an international conference
Valeria Pannunzio1, Alexander Komashie1, Sebastian Walsh1, Richard Milne1, Timoleon Kipouros1, Guillaume Lamé2, Anja Maier3,4, Carol Brayne1, P. John Clarkson1
1University of Cambridge, United Kingdom; 2CentraleSupélec, France; 3University of Strathclyde, United Kingdom; 4Technical University of Denmark, Denmark
This contribution departs from an existing model, the Design Framework for Systems-of-Systems Resilience, to explore systems resilience issues across the health, environmental, and economic domains. The reported research activities include 1) a rapid review to collect a set of systems indicators and 2) a design workshop employing causal loop diagramming to map expected causal influences between indicators. Through this exercise, we examine key themes in this research domain and outline directions for further enquiry, while involving members of the design research community in an open dialogue.
Designing for systems-of-systems resilience: from the individual to the planet
Valeria Pannunzio, Timoleon Kipouros, Amber Khan, Laurie Friday, Carol Brayne, P. John Clarkson
University of Cambridge, United Kingdom
This contribution builds on the Design Framework for System-of-Systems Resilience to investigate the potential of a new systems resilience measuring approach inspired by the Frailty Index. To explore this research direction, we provide a brief overview of the evolution of the notion of resilience, offer a characterisation of systems resilience as an opposite of systems frailty, and perform a rapid review to identify and inspect existing multi-domain indices of community resilience. Finally, we suggest piloting the proposed system-of-systems resilience index in the Fens in the United Kingdom.
A tradespace exploration approach for changeability assessment from a system-of-systems perspective: application from the construction machinery industry
Raj Jiten Machchhar, Carl Nils Konrad Toller Melén, Alessandro Bertoni
Blekinge Institute of Technology, Sweden
The rapid development of new technologies such as electrification, autonomy, and other contextual factors pose significant challenges to development teams in balancing competing aspects while developing value-robust solutions. One approach for achieving value robustness is designing for changeability. This paper presents a tradespace exploration from a Systems-of-Systems perspective to facilitate changeability assessment during early design stages. The approach is further demonstrated on a fleet of haulers operating in a mining site.
Principles for the design of system of systems exemplified using modularisation
Matthias Günther1, Tobias Seidenberg1, Harald Anacker1, Roman Dumitrescu1,2
1Fraunhofer IEM, Germany; 2Heinz Nixdorf Institute, Paderborn University, Germany
In the context of system of systems (SoS) engineering, the incorporation of design principles is critical to guide the engineering process. This paper presents a systematic literature review to synthesize a list of principles tailored for SoS. 26 principles were identified as generic principles and 39 were mapped to the specific challenges in SoS engineering. Through an evaluation using the principle of modularisation in the design of a charging infrastructure, the study offers insights into the real-world effectiveness of these principles, showing their relevance in SoS engineering tasks.
Bridging simulation granularity in system-of-systems: conjunct application of discrete element method and discrete event simulations in construction equipment design
Mubeen Ur Rehman, Raj Jiten Machchhar, Alessandro Bertoni
Blekinge Institute of Technology, Sweden
The paper addresses a critical challenge in System-of-Systems (SoS) simulations arising from the different granularity levels in SoS simulations, integrating non-coupled Discrete Element Method results into SoS-level Discrete Event Simulations using surrogate modeling. Illustrated with a wheel loader bucket use-case in mining, it enhances early design decision-making and lays the groundwork for improving SoS simulations in construction equipment design. This paves the way for broader research and application across diverse engineering design domains.
AI-based analysis and linking of technical and organisational data using graph models as a basis for decision-making in systems engineering
Sebastian Katzung1, Hüseyin Cinkaya1, Umut Volkan Kizgin2, Alexander Savinov3, Julian Baschin2, Thomas Vietor2
1ENBACE GmbH, Germany; 2Technische Universität Braunschweig, Germany; 3Siemens Mobility GmbH, Germany
The increased complexity of development projects surpass the capabilities of existing methods. While Model Based Systems Engineering pursues technically holistic approaches to realize complex products, aspects of organization as well as risk management, are still considered separately. The identification and management of risks are crucial in order to take suitable measures to minimize adverse effects on the project or the organization. To counter this, a new graph-based method and tool using AI, tailored to the needs of complex development projects and organizations is introduced here.
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