Robust Design of a Collaborative Platform for Model-Based System Engineering: Experience from an Industrial Deployment

Ponsard, Christophe; Darimont, Robert; Touzani, Mounir

doi:10.1007/978-3-030-32065-2_23

Cited by 1 publication

(1 citation statement)

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“…is captures the suitability of the model for the task. e literature regarding model management in MBSE and software engineering has focused on model management platform [26], model repository building methods [27], and so on, but has not provided a method for the evaluation of model value for the task. is study applies an advantage-number-based analytical technique to evaluate the models to be assigned from the perspective of value and, accordingly, preferentially filters the models to establish a design-task-oriented preferred model set.…”

Section: Introductionmentioning

confidence: 99%

A Design-Task-Oriented Model Assignment Method in Model-Based System Engineering

Wang

Liao

Guo

et al. 2020

Mathematical Problems in Engineering

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In model-based system engineering (MBSE), reuse of existing models in the development of a new system can be advantageous. Automatic assignment of existing models to each design task within a design task set has been proven to be feasible. However, while several studies have discussed the significance of models in MBSE and methodologies for models reuse, solving the model reusability problem through a model assignment method has not been discussed. Additionally, a significant challenge in model assignment is to address the conflict between the maximization of the model value summations, which are yielded by assigning the models to a design task set, and the minimization of the execution cycle of the task set. This study (a) proposes a design-task-oriented model assignment method that establishes a multiobjective model, based on a model assignment integration framework, and (b) designs a differential-evolution-combined adaptive nondominated sorting genetic algorithm-II to provide an optimal tradeoff between maximizing the total model values and minimizing the execution cycle of the task set. By comparing the performance of the algorithm in resolving the assignment of models to a design task set with those of two conventional algorithms in a phased-array radar development project, the algorithm’s performance and promotion of system development are verified to be superior. The new method can be applied for developing model scheduling software for MBSE-compliant product development projects to improve using effects of the models and development cycle.

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Section: Introductionmentioning

confidence: 99%