Model-based-systems-engineering for conceptual design: An integrative approach

 Summary of "Model-based-systems-engineering for conceptual design: An integrative approach" by Sharon Shoshany-Tavory, Eran Peleg, Avigdor Zonnenshain, Gil Yudilevitch in the Systems Engineering Journal of INCOSE https://incose.onlinelibrary.wiley.com/doi/10.1002/sys.21688?af=R

The article "Model-based-systems-engineering for conceptual design: An integrative approach" describes a methodology for integrating model-based systems engineering (MBSE) with conceptual design. The paper highlights the need for an integrative approach to bridge the gap between systems engineering and conceptual design, which are often treated as separate and distinct activities.

The authors propose a six-step approach that involves the creation of a common language and ontology for the design, the development of a model-based representation of the system, and the use of simulation and analysis to evaluate the design. The approach also emphasizes the importance of stakeholder involvement throughout the process.

The authors illustrate the approach using an example of designing an autonomous vehicle. They show how the approach can be used to integrate the various subsystems of the vehicle, such as sensing, decision-making, and actuation.

The authors use the example of designing an autonomous vehicle to illustrate the application of their proposed approach for integrating model-based systems engineering (MBSE) with conceptual design. The example demonstrates how the approach can be used to integrate various subsystems of the vehicle, such as sensing, decision-making, and actuation.

The authors begin by developing a common language and ontology for the design, which includes identifying the stakeholders, their objectives, and the requirements of the system. They then create a model-based representation of the system using a variety of modeling techniques, such as statecharts, block diagrams, and SysML diagrams.

The model-based representation of the system is used to simulate and analyze the performance of the design, which enables the identification of potential issues and the optimization of the design. For example, the authors simulate the behavior of the sensing subsystem under various driving scenarios, such as detecting a pedestrian crossing the street or a vehicle changing lanes.

The authors also use the model-based representation to evaluate the trade-offs between various design choices. For instance, they consider the trade-off between the accuracy of the sensing subsystem and its cost, and evaluate the impact of this trade-off on the overall performance of the vehicle.

Overall, the example of designing an autonomous vehicle demonstrates the application of the proposed approach for integrating MBSE with conceptual design. It illustrates how the approach can be used to integrate various subsystems of a complex system and how it can be used to simulate and analyze the performance of the design.

 Overall, the article emphasizes the importance of early-stage MBSE in the conceptual design process to improve the efficiency and effectiveness of system design. It provides a detailed methodology for integrating MBSE and conceptual design and illustrates its application in a real-world example.