2018
DOI: 10.1002/j.2334-5837.2018.00572.x
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Enhancing Automated Trade Studies using MBSE, SysML and PLM

Abstract: One of the critical tasks of Systems Engineering MBSE methodology is execution of Trade Studies. Trade Studies are key to identifying the best‐in‐class architectural and realization alternatives. These studies often rely on physical characteristics of the available system elements represented by the “P” in the core system elements called RFLP (Requirements‐Functional‐Logical‐Physical). Such realization alternatives are not always easy to find for the Systems Engineers and often require tedious manual definitio… Show more

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Cited by 13 publications
(6 citation statements)
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“…With the PLM backbone being supplied by a dedicated supplier, the end result is a high dependence on that supplier. Examples of this pattern can be found in Banaj et al (2016) and Chadzynski et al (2018).…”
Section: Plm Backbonementioning
confidence: 76%
“…With the PLM backbone being supplied by a dedicated supplier, the end result is a high dependence on that supplier. Examples of this pattern can be found in Banaj et al (2016) and Chadzynski et al (2018).…”
Section: Plm Backbonementioning
confidence: 76%
“…MBSE and PLM integration is a topic that keeps on gaining momentum. In the past years, there has been work on how to integrate MBSE and PLM throughout parametric models as in [4], also how to automate trade studies using MBSE and PLM [5], how MBSE and PLM industrial integration is a need for mission-critical systems [6], and incorporation of DT technology into MBSE [7].…”
Section: Introductionmentioning
confidence: 99%
“…Alternative, a backbone managing information edited by multiple front-end applications. Syndelia by InterCax is an example of the latter (Banaj et al 2016), a standards based solution is proposed in (Rosén 2006), and an ARAS backbone is explored in (Chadzynski et al 2018). For an organization, both approaches result in a strong dependency on the supplier of the monolith or backbone capability.…”
Section: Architecting For Federated Plmmentioning
confidence: 99%