Tailoring Model-Based Systems Engineering concepts for industrial application

Tschirner, Christian; Dumitrescu, Roman; Bansmann, Michael; Gausemeier, J.

doi:10.1109/syscon.2015.7116731

Cited by 8 publications

(3 citation statements)

References 15 publications

(8 reference statements)

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“…However, there are multiple sides to the story. On the one hand, we have experienced an incredible innovation leap in recent years (Tschirner et al 2014). We have moved from mechanics to mechatronics and finally to intelligent and interconnected systems such as cyber-physical systems (CPS), smart products and systems of systems (SoS) (Bricogne et al 2016;Maier 1996; Pereira Pessôa and Jauregui Becker 2020).…”

Section: Introductionmentioning

confidence: 99%

“…We have moved from mechanics to mechatronics and finally to intelligent and interconnected systems such as cyber-physical systems (CPS), smart products and systems of systems (SoS) (Bricogne et al 2016;Maier 1996; Pereira Pessôa and Jauregui Becker 2020). On the other hand, these advancements are not without consequences: complexity has disproportionately and quickly risen in many areas (Tschirner et al 2014) The mind map of Fig. 1, non-exhaustively summarizes these consequences of complexity, among which we have increased expectations on systems (adaptation, emergence, intelligence, interconnectedness, etc.)…”

Section: Introductionmentioning

confidence: 99%

“…Fig.1Mind map describing innovation needs vs. complexity symptoms. Based onSheard and Mostashari (2010) andTschirner et al (2014) …”

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confidence: 99%

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Engineering complexity beyond the surface: discerning the viewpoints, the drivers, and the challenges

2023

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Complexity is often regarded as a “problem” to solve. Instead of attempting to solve complexity, we follow systems engineering practices and switch back to the problem domain, where a major obstacle is the impossibility to universally define complexity. As a workaround, we explored complexity characterization and its existing shortcomings, including: lack of standardization, inconsistent semantics, system-centricity, insufficiently transparent reasoning, and lack of validation. To address these shortcomings, we proposed a compilatory framework to characterize complexity using the Five Ws information-gathering method. The answer to the WHO question proposed four complexity viewpoints; the answer to the WHY question proposed a two-dimensional structure for complexity drivers; and the answer to the WHAT question derived generalized complexity challenges. As a preliminary step to show the potential of the framework to characterize complexity, we used and validated it as a tool to structure general literature related to complexity. In general, our findings suggest that papers with complexity solutions do not frame their research within the complexity problem domain, hindering the contribution evaluation. Through the viewpoints, we identified general research gaps of six solution directions. From the drivers, we noted three observations in the discourse of complexity origins: (1) a system-driven tendency, (2) a preference for concreteness vs. abstraction, and (3) an unclear distinction between origins and effects. Through the challenges’ findings we explored two hypotheses: (1) a system-centric preference; and (2) a solution-oriented vision, both of which were supported by the results (most challenges relate to the system viewpoint and challenges are defined based on solution directions).

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Engineering complexity beyond the surface: discerning the viewpoints, the drivers, and the challenges

2023

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Model‐based analysis and specification of functional requirements and tests for complex automotive systems

Wiecher,

Mandel,

Günther

et al. 2024

Systems Engineering

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The specification of requirements and tests are crucial activities in automotive development projects. However, due to the increasing complexity of automotive systems, practitioners fail to specify requirements and tests for distributed and evolving systems with complex interactions when following traditional development processes. To address this research gap, we propose a technique that starts with the early identification of validation concerns from a stakeholder perspective, which we use to systematically design tests that drive a scenario‐based modeling and analysis of system requirements. To ensure complete and consistent requirements and test specifications in a form that is required in automotive development projects, we develop a Model‐Based Systems Engineering (MBSE) methodology. This methodology supports system architects and test designers in the collaborative application of our technique and in maintaining a central system model, in order to automatically derive the required specifications. We evaluate our methodology by applying it at KOSTAL (Tier1 supplier) and within student projects as part of the masters program Embedded Systems Engineering. Our study corroborates that our methodology is applicable and improves existing requirements and test specification processes by supporting the integrated and stakeholder‐focused modeling of product and validation systems, where the early definition of stakeholder and validation concerns fosters a problem‐oriented, iterative and test‐driven requirements modeling.

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Model-Based Systems Engineering in Smart Manufacturing - Future Trends Toward Sustainability

Bataleblu,

Rauch,

Cochran

2023

Lecture Notes in Networks and Systems

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Tailoring Model-Based Systems Engineering concepts for industrial application

Cited by 8 publications

References 15 publications

Engineering complexity beyond the surface: discerning the viewpoints, the drivers, and the challenges

Engineering complexity beyond the surface: discerning the viewpoints, the drivers, and the challenges

Model‐based analysis and specification of functional requirements and tests for complex automotive systems

Model-Based Systems Engineering in Smart Manufacturing - Future Trends Toward Sustainability

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