Environment modeling for evaluating system variants in model-based systems engineering

White, Dustin; Sahlab, Nada; Jazdi, Nasser; Weyrich, Michael

doi:10.1016/j.procir.2021.11.126

Cited by 2 publications

(1 citation statement)

References 6 publications

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“…Funktionsorientierung bekommt eine wachsenede Relevanz in der Entwicklung cyberphysischer Systeme und wird in der Betrachtung von Varianz nicht ausreichend berücksichtigt. Aktuell exisitiert keine Methode, um Ingenieure bei der frühzeitigen Abbildung von Varianz von Funktionen und Lösungsprinzipien zu unterstützen [11]. Aktuelle Ansätze des modellbasierten Variantenmanagements bilden die Varianz vor allem auf physischer Ebene ab, basierend auf Stücklisten für explizite Varianten [4,12].…”

Section: Motivationunclassified

Modeling and analysis of functional variance of complex technical systems

Menninger¹,

Wiechel²,

Rackow³

et al. 2022

DS 119: Proceedings of the 33rd Symposium Design for X (DFX2022)

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Complexity of variances in systems leads to challenges in structuring and in making development decisions. Models can collect system information to make them available and transparent. Currently, no approach to model the variance of systems along relevant engineering artifacts exists. This research aims to develop a consistent variant modeling approach: In a literature review (1), relevant approaches in model-based variant management are identified to derive requirements for variant modelling (2). Based on the requirements, approaches are evaluated in a matrix (3). Since no approach satisfies all requirements, one approach is extended (4). For evaluation purpose (5), applicability of the approach is demonstrated and assessed by experts. The result is a modeling method for variant modeling.

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Section: Motivationunclassified