Premium
Applying Bayesian Networks to TRL Assessments – Innovation in Systems Engineering
Author(s) -
Austin Marc F.,
Homberger Cheyne,
Ahalt Virginia,
Doolittle Erin,
Polacek George A.,
York Donald M.
Publication year - 2017
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2017.00451.x
Subject(s) - bayesian network , technology readiness level , metric (unit) , maturity (psychological) , computer science , bayesian probability , scale (ratio) , artificial intelligence , systems engineering , industrial engineering , engineering management , machine learning , operations research , engineering , operations management , psychology , developmental psychology , physics , quantum mechanics
Currently, Technology Readiness Assessments (TRAs) are used in determining the maturity of the Critical Technology Elements (CTEs) of a system as it moves forward in the system development life cycle. The TRA method uses Technology Readiness Levels (TRLs) as the decision metric. TRL values are assessed and determined by Subject Matter Experts (SMEs). Since expert evaluators often differ in their judgment when scoring a system element against the TRL scale criteria, this paper argues for the use of a Bayesian network model to provide a mathematical method to consistently combine and validate the judgment of these SMEs and increase the confidence in the determination of the readiness of system components and their technologies.