Measures of Effectiveness Analysis of an Advanced Air Mobility Post–Disaster Response System

Use of measures of effectiveness (MOE) analysis in exploring candidate systems or alternatives has been the subject of much debate in the systems engineering discipline, as some authors have noted. In this work, methods for MOE analysis are revisited as they pertain to an advanced air mobility platform, first by using the traditional approach, which involves the application of the Pugh matrix, and second by proposing an approach that involves a combination of two (2) methods, namely the Monte Carlo method (MCM) and the analytical hierarchy process (AHP), in order to evaluate and rank the preferred alternative from a selection of candidate systems. The latter method is termed the Monte Carlo–analytical hierarchical hybrid process (MC–AHHP). The results obtained from the application of both approaches demonstrate that the MC–AHHP is a less subjective, more objective, data-driven, and quantitative measure for MOE analysis compared to the erstwhile Pugh matrix method. While the Pugh matrix ranked the SAR AAM as first overall among seven (7) alternatives, the MC–AHHP ranked the same second among three (3) alternatives. The subsequent verification and validation process showed that the MC–AHHP approach resulted in a degree of consistency value of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>0.083</mn></mrow></semantics></math></inline-formula>, where <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>C</mi><mi>I</mi><mo>/</mo><mi>R</mi><mi>I</mi><mo><</mo><mn>0.10</mn></mrow></semantics></math></inline-formula> represents an acceptable level of consistency. Thus, the MC–AHHP approach is recommended as a viable decision-making tool for adoption by systems engineering practitioners.