Assessing the Self-Healing Technology Using Novel Technology Impact Forecasting

Low technology readiness level (TRL) technologies are attractive to the aerospace industry because their maturation cycles can happen simultaneously with the development lifecycle of the aircraft. However, due to the limited knowledge about a new technology in system evaluation, a low TRL technology’s high potential is counterbalanced by its inherent high risk and high uncertainty. As a result, the assessment of the potential impact of low TRL technologies on a new system is exceedingly difficult. In this paper, a modified technology impact forecasting (TIF) methodology has been proposed that incorporates the novel use of possibility distributions to more accurately quantify the potential of a low TRL technology on a baseline system. The proposed method has been demonstrated through a case study that considers composite self-healing technologies (i.e., microcapsule-based and one-dimensional vascular-based self-healing materials) as a representative low TRL technology, and quantifies the impact of infusing this set of technology onto a notional commercial aircraft system. The results show that, compared with evaluation using a traditional TIF framework, the variability using possibility distributions is significantly reduced for the same system responses. This reduced variability decreases uncertainty, which implies further reduced risk.