A value‐driven, integrated approach to Model‐Based Product Line Engineering

Navas, Juan Sebastián Gómez; Bonnet, Stéphane; Voirin, Jean‐Luc; Góngora, Hugo G. Chalé

doi:10.1002/j.2334-5837.2021.00828.x

Cited by 1 publication

(2 citation statements)

References 8 publications

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“…∑ 𝐹 𝑥 = 𝑀 × 𝑎 = 𝑓 − 𝑚 × 𝑔 𝑥 (8) 𝑀 × 𝑎 = 𝑇/𝑅 − 𝑀 × 𝑔 × 𝑠𝑖𝑛(θ) (9) 𝑇 = 𝑅 × 𝑀 × (𝑎 + 𝑔 × 𝑠𝑖𝑛(θ)) (10) The Torque value in (10) is the expression we modelled for one wheel. In (11), we add N as the number of wheels, which divides the torque required for the system:…”

Section: Cmentioning

confidence: 99%

“…While most common system engineering publications rely on MBSE and SysML 1.3 principles to provide pragmatic models [6] and to share high-level information, the inclusion of physical constraints are seldom expressed in system models. Furthermore, the processes exposed for MBPLE using variants at high level with Cameo Modeler [7] or ARCADIA/Capella [8] do not include automated connections that would take mechanical constraints impacts on system overall decisions.…”

Section: Introductionmentioning

confidence: 99%

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Tackling Optimization and System-Driven Engineering in Coupling Physical Constraints with MBSE: The Case of a Mobile Autonomous Line of Products

Brisacier-Porchon,

Hammami

2024

The Proceedings of the 2023 Conference on Systems Engineering Research

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The main goal of product line engineering is to build complex system architecture at the best quality, cost, resource ratio. The return on investment in terms of assessment is however not trivial, as systems to build rise in complexity. Moreover, the perspective of system of systems engineering that set up both historic and new systems in capabilities, and the introduction of more and more autonomous systems in architectures makes the anticipation of return on investment impossible to achieve without computer assistance. The necessary tools to assess as precisely as possible also involve a wide exploration of possibilities in an ever-changing context. The absence of mechanical or multi physical aspects in SysML-based tools, either in its version 1.3 or 2.0, makes it inefficient in representing or simulating robotic systems or system of system engineering. This article explains the benefits of tackling a classic Multi-Objective Knapsack Problem (MOKP) to the UGV product line items selection using a seamless system architecting toolchain. The association of MBSE (Model-based System Engineering), OR (Operation Research) and MBD (Model Based design) that generated various designs is presented. Our results in system engineering in UGV presents a Pareto Front of trade-offs that can count as numerous possibilities that sole MBSE or separate MBD simulation could not have represented as the best in the sense of . The simultaneous variations in both hardware and mechanical design show was entirely automated using standard tools with no redesign. This shows that seamless automations should pave the future of system engineering tools. With Operation research and Systems engineering tackling methods, our model upscale to real systems will shape System-Driven Engineering that will require new skills in system validation and verification and simulation analytics.

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