Abstract
Modular plant design requires assessing whether independently characterized process requirements and module capabilities are compatible-a challenge that established methods address incompletely. Feasibility and flexibility analysis, as well as Quality by Design, typically assume integrated single-domain models where all variables belong to one coherent description, yet modular design involves domains that originate from different sources, evolve independently, and connect through interface variables. This work proposes Quantified Constraint Satisfaction Problems (QCSPs) as a formulation for interface-level suitability assessment: universal quantification encodes properties that must hold across their entire admissible range (e.g., physical properties, uncertain or environment-dependent characteristics requiring robustness), while existential quantification encodes variables where at least one feasible value must exist (e.g., critical process parameters, control inputs, configuration options). By operating over domain interfaces rather than requiring integrated system models, the formulation accommodates heterogeneous information sources within a common problem specification, with uncertainty handled through probabilistic intervals governed by a global confidence threshold. The framework supports both finite-domain solving on pre-evaluated datasets and numeric solving through on-demand model evaluation. A bioreactor suitability case study provides proof-of-concept, illustrating how the framework accommodates realistic problem complexity and offering initial observations on method selection trade-offs.