Engineering Systems Matrix: An organizing framework for modeling large-scale complex systems

The scope and complexity of engineered systems are ever-increasing as burgeoning global markets, unprecedented technological capabilities, rising consumer expectations, and ever-changing social requirements present difficult design challenges that often extend beyond the traditional engineering para...

Full description

Bibliographic Details
Main Authors: Bartolomei, Jason E. (Contributor), Hastings, Daniel E. (Contributor), de Neufville, Richard (Contributor), Rhodes, Donna H. (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Engineering Systems Division (Contributor), MIT Sociotechnical Systems Research Center (Contributor)
Format: Article
Language:English
Published: Wiley-Blackwell Pubishers, 2012-04-19T15:26:51Z.
Subjects:
Online Access:Get fulltext
Description
Summary:The scope and complexity of engineered systems are ever-increasing as burgeoning global markets, unprecedented technological capabilities, rising consumer expectations, and ever-changing social requirements present difficult design challenges that often extend beyond the traditional engineering paradigm. These challenges require engineers and technical managers to treat the technological systems as a part of a larger whole. Existing system modeling frameworks are limited in scope for representing the information about engineering systems. This paper presents a conceptual framework and an improved modeling framework for engineering systems. Its value is that it allows engineers and managers an improved means to visually arrange information and structure discourse in a way that facilitates better systems engineering. It augments the existing literature by providing a clear and concise framework for an engineering system, and provides a methodology for engineers to tag and organize systems information in ways that allow for better collection, storage, processing, and analysis of systems engineering data.