Configuration solving is essential in product configuration because it supports decisions on selecting final configuration alternatives to satisfy stakeholders' preferences. However, the inherent interaction of product Design Requirements (DRs) and multiple stakeholders involved lead to three limitations in developing an appropriate configuration solving model: 

• (i) the existing models have limitations in balancing the tractability of the model and the diversity of interactions; 
• (ii) it is impractical to assume that different stakeholders have consistent preferences for the alternatives, and directly removing inconsistent preferences can lead to the loss of preference information;
• (iii) the representativeness of preference functions built from incomplete preference information is doubtful.

To address these limitations, a robust product configuration ranking approach is proposed: 

• first, the Choquet integral with the k-interactive fuzzy measure is applied to evaluate alternatives with DRs’ interactions, improving the tractability by reducing the number of parameters and related constraints; 
• second, an interactive method of identifying a minimum set of adjustable inconsistent preferences is proposed to adjust them among different stakeholders, avoiding the preferences loss and ensuring the trade-off among stakeholders; 
• third, a representative ranking model based on the k-interactive Choquet integral and nonadditive robust ordinal regression is proposed to select the robust alternative concerning individual and group stakeholders' preferences. 

To validate its feasibility and effectiveness, the proposed approach is applied to an example of configuration solving for a robotic manufacturing system.