Model-Based Systems Engineering Methods

In general, contemporary organizations are designing complex systems as they need to avoid delays and cost overruns to stay competitive. Although undesired, they frequently occur when the complexity of a system has been underestimated.

Among other factors, a system’s complexity depends on its number of components and its number of inter-component dependencies that can be multidisciplinary. Complex systems have large numbers of subsystems with highly integrated, complex, and intelligent structural and behavioral autonomous elements from multiple domains such as mechanical, electrical, control, and software [1].

A Model-Based Systems Engineering (MBSE) approach is transforming the study of the field of Systems. They offer techniques to aid in developing complex systems by aiming to reduce design errors, reduce cost through prevention of costly rework, and improve system quality and project performance over traditional systems engineering techniques [2]. They are substituting conventional methods (NASA-based) to help engineers deal with the complexity of complex systems. They perform comprehensive analysis at the foundational systems level necessary to realize these systems.

Using MBSE reduces the risk of late design defects by focusing on early conceptual design and preliminary design stages of a project. The cost associated with fixing errors increases the later they are discovered in the design process.

Model-based systems engineering methods are cheaper and more straightforward, therefore help to the current low-budget and agile development programs. Thus, a project using MBSE can achieve its most significant cost savings by finding errors early in the project.

.[1] Younse, P.; Cameron1, J.; Bradley, T. Comparative analysis of a model-based systems engineering approach to atraditional systems engineering approach for architecting a robotic spacesystem through knowledge categorization — Mobility and Robotic Systems, Jet Propulsion Laboratory of California Institute of Technology, Pasadena, California, USA 2021.

[2] Roy Butler and Michael Pennotti. The evolution of software and its impacton complex system design in robotic spacecraft embedded systems.ProcediaComputer Science, 16:747–756, 2013