Increased System Consistency through Incorporation of Coupling in Value‐Based Systems Engineering. Issue 1 (24th April 2017)

• Record Type: Journal Article
• Authors: Kannan, Hanumanthrao; Mesmer, Bryan L.; Bloebaum, Christina L.
• Is Part Of: Systems engineering. Volume 20:Issue 1(2017)
• Page Start: 21
• Page End: 44
• Publication Date: 2017-04-24
• Subjects: value‐driven design -- system consistency -- multidisciplinary design optimization; Systems engineering -- Periodicals; 620.0011
• DOI: 10.1002/sys.21377
• Languages: English
• ISSNs: 1098-1241

Abstract

ABSTRACT: The design of large‐scale complex engineered systems involves hundreds to thousands of designers making decisions across different organizations and at different levels of organizational hierarchy. These systems are designed within a systems engineering framework, where requirements are used as proxies for stakeholder preference. Requirements drive the development process and are flowed across organizations and down through the organizational hierarchies. Value‐driven design offers a new perspective where the preferences of the stakeholder are communicated directly through a decomposable value function, rather than decomposable requirements, thereby enabling improved consistency in system preference. This paper investigates two key aspects of achieving improved system consistency through a value‐based systems engineering approach, using a commercial satellite system as a testbed. The paper first contrasts the diverse systems that result from traditional requirements‐based versus preference‐based formulations, demonstrating how a value‐based approach aids in capturing the true preferences of the stakeholder in problem formulation. The paper demonstrates the importance of using system couplings to enable an improved accuracy for value function decomposition. The paper demonstrates that ensuring system analysis consistency through use of system sensitivities can overcome issues pertaining to: dependencies of attributes; inadequately capturing system interactions; and direct modification of attributes to determine value impact.