An integration-centric approach is proposed to handle inadequate information in the system readiness level （SRL） assessment using the evidential reasoning （ER） algorithm. Current SRL assessment approaches cannot b...An integration-centric approach is proposed to handle inadequate information in the system readiness level （SRL） assessment using the evidential reasoning （ER） algorithm. Current SRL assessment approaches cannot be applied to handle inadequate information as the input. The ER-based approach is proposed to synthesize inadequate input information and an integration-centric perspective is applied to reduce the computational complexity. Two case studies are performed to validate the efficiency of the proposed approach. And these studies are also performed to study how the inadequate information will affect the assessment result. And the differences caused by the system＇s structure. The importance of the system＇s structure in the SRL assessment is demonstrated and the contributions made in this study are summarized as conclusions.展开更多
Contemporary system maturity assessment approaches have failed to provide robust quantitative system evaluations resulting in increased program costs and developmental risks.Standard assessment metrics,such as Technol...Contemporary system maturity assessment approaches have failed to provide robust quantitative system evaluations resulting in increased program costs and developmental risks.Standard assessment metrics,such as Technology Readiness Levels（TRL）,do not sufficiently evaluate increasingly complex systems.The System Readiness Level（SRL）is a newly developed system development metric that is a mathematical function of TRL and Integration Readiness Level（IRL） values for the components and connections of a particular system.SRL acceptance has been hindered because of concerns over SRL mathematical operations that may lead to inaccurate system readiness assessments.These inaccurate system readiness assessments are called readiness reversals.A new SRL calculation method using incidence matrices is proposed to alleviate these mathematical concerns.The presence of SRL readiness reversal is modeled for four SRL calculation methods across several system configurations.Logistic regression analysis demonstrates that the proposed Incidence Matrix SRL（IMSRL）method has a decreased presence of readiness reversal than other approaches suggested in the literature.Viable SRL methods will foster greater SRL adoption by systems engineering professionals and will support system development risk reduction goals.展开更多
基金supported by the National Natural Science Foundation of China (70901074 71001104)
文摘An integration-centric approach is proposed to handle inadequate information in the system readiness level （SRL） assessment using the evidential reasoning （ER） algorithm. Current SRL assessment approaches cannot be applied to handle inadequate information as the input. The ER-based approach is proposed to synthesize inadequate input information and an integration-centric perspective is applied to reduce the computational complexity. Two case studies are performed to validate the efficiency of the proposed approach. And these studies are also performed to study how the inadequate information will affect the assessment result. And the differences caused by the system＇s structure. The importance of the system＇s structure in the SRL assessment is demonstrated and the contributions made in this study are summarized as conclusions.
文摘Contemporary system maturity assessment approaches have failed to provide robust quantitative system evaluations resulting in increased program costs and developmental risks.Standard assessment metrics,such as Technology Readiness Levels（TRL）,do not sufficiently evaluate increasingly complex systems.The System Readiness Level（SRL）is a newly developed system development metric that is a mathematical function of TRL and Integration Readiness Level（IRL） values for the components and connections of a particular system.SRL acceptance has been hindered because of concerns over SRL mathematical operations that may lead to inaccurate system readiness assessments.These inaccurate system readiness assessments are called readiness reversals.A new SRL calculation method using incidence matrices is proposed to alleviate these mathematical concerns.The presence of SRL readiness reversal is modeled for four SRL calculation methods across several system configurations.Logistic regression analysis demonstrates that the proposed Incidence Matrix SRL（IMSRL）method has a decreased presence of readiness reversal than other approaches suggested in the literature.Viable SRL methods will foster greater SRL adoption by systems engineering professionals and will support system development risk reduction goals.
