Use of Bayesian Networks to understand sustainability requirements

Sustainability is a key requirement in contemporary engineering design, but it is difficult to quantify due to its multidimensionality. We propose the application of Bayesian Networks for modeling the cause and effect of engineering systems and their environment. Emphasis is placed on capturing the impact on sustainability indicators of design decisions. These include the performance of the system, its economic viability in terms of cost, and its environmental and societal impacts. The method leverages data from simulation models, enabling the designer to perform assumption-free inferences on the variables at play.