On the design of large systems subject to uncertainty

ABSTRACT Top-down development following the V-model of systems engineering can help to deal effectively with uncertainty in systems design without a particular uncertainty model. Often in industrial practice, however, concrete design steps are difficult to identify using the general theory – and the V-model remains a theoretical construct. This paper presents a simple but effective framework for systems engineers to connect the V-model theory with quantitative design methods, thus enabling a structured process for the systematic distributed design of large multi-disciplinary systems subject to uncertainty. The framework proposed includes three distinct steps: first, the system structure is modelled by specifying all relevant dependencies between system variables (i.e. design variables and objective quantities) in a hierarchical dependency graph. This simple formalism provides a concrete structure for the design process. Second, quantitative bottom-up mappings between system variables are established by physical or mathematical models. Third, quantitative top-down mappings are used to provide regions of permissible designs, so-called solution spaces. They encompass variability related to epistemic uncertainty and are maximised for the integration of requirements from different disciplines. They are computed by existing numerical algorithms or a projection technique. Several vehicle design problems demonstrate the general applicability and the effectiveness of the approach.