MIT Strategic Engineering
Systems Architecture and Engineering
Systems Architecture is a field of study and practice that translates stakeholder needs and goals into a concept that specifies the main functions, structure and behavior of the system. Systems Architecting uses abstractions and conceptual design methods to decrease ambiguity, enhance creativity and manage complexity during early system and product development.
Key research topics in system architecture are stakeholder analysis, requirements formulation and goal definition, functional decomposition, form-function mapping, modularity quantification and complexity management, among others. Network and graph theory, abstract algebra as well as object-process methodology (OPM) are key methods that support systems architecting.
Systems Engineering is a field of research and practice that focuses on transitioning early system concepts and architectures coming out of the systems architecting process to implementable systems, products and services.
Systems engineering research focuses on methods and tools for balancing competing performance requirements with lifecycle cost, infusing new technologies, managing safety margins and ensuring system integrity over a large range of operating conditions. We find the "V" model of systems engineering to be useful (albeit not perfect).
Our contributions to systems architecture and engineering include:
- Isoperformance: a methodology for obtaining sets of designs that meet a vector of desired performance targets, while minimizing secondary cost and risk objectives
- SMI - Singular Value Modularity Index, a measure of modularity in systems based on singular value decomposition (SVD) of the underlying system design structure matrix (DSM)
- Augmented network representations of systems using graph theory with multi-partite node and weighted edge representations
- A functional classification of complex systems
- TDN (Time-expanded decision networks) - a method for designing evolvable systems in an uncertain environment
- CPI - Change Propagation Index for characterizing subsystems as absorbers, multipliers or carriers of engineering change
- P-point analysis for quantifying where systems reach an inflection point (or tipping point) in terms of excessive complexity that does not yield comensurate benefits in performance or robustness