Detecting antifragile decisions and models lessons from a conceptual analysis model of Service Life Extension of aging vehicles

Detecting antifragile decisions and models lessons from a conceptual analysis model of Service Life Extension of aging vehicles This paper explores how the concept of Antifragility applies to decision making and to the design of effective decision-support models. The context of this research is a conceptual analysis of several Service Life Extension Program (SLEP) options for aging vehicles. In this context, a decision authority would decide how much service life to buy for each vehicle in order to achieve a target Out of Service Date (OSD). Endemic uncertainties, ambiguities, and errors pervade this potentially high-stakes decision making. We review the concept of Antifragility and pay particular attention to its measurement, its relationships to robustness and fragility, and ultimately how it provides indication of model maturity. We offer a technique of scenario development that uses factor combinations to describe a scenario space, which is based fundamentally on the Design of Experiments (DOE) method. Since the scenario elements are highly modular, the scenario space can be changed in response to stakeholder refutations. We show how the boundaries of the scenario space can be explored and sanitized of BlackSwans, thus cultivating antifragile models and courses of action.