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Mitigating Integration Risks in Complex Systems
Author(s) -
Austin Marc F.,
Doolittle Erin,
Polacek George A.,
Ahalt Virginia,
Homberger Cheyne,
York Donald M.
Publication year - 2018
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2018.00503.x
Subject(s) - computer science , system integration , software deployment , bayesian network , maturity (psychological) , metric (unit) , risk analysis (engineering) , systems engineering , artificial intelligence , engineering , software engineering , operations management , business , database , psychology , developmental psychology
In the Age of Globalization, integration is one of the primary areas of risk for today's complex system development programs. Integration failures continue to be one of the main reasons for unsuccessful system deployments. The Integration Readiness Level (IRL) is a new system metric developed to measure the integration maturity between two system components. IRLs, in conjunction with Technology Readiness Levels (TRLs), form the basis for determining the readiness of a system for deployment. The IRL represents the systematic analysis of the interactions between system components and provides a consistent comparison of the maturity between integration points. IRLs provide a means to reduce the risk involved in maturing and integrating system components in complex environments. We first present a methodology for determining the integration readiness of a system and its components and then describe the construction of a Bayesian network model for assessing IRLs. The IRL Bayesian network model provides a mathematical method to consistently combine and validate the judgment of experts assessing integration and increase the confidence in the determination of the integration readiness of a system and its components.