This paper presents a conceptual approach for decision support applied in a collaborative complex system design project. The approach takes advantage of the use of Similarity-based Formal Concept Analysis (SFCA) to classify, visualize, and explore simulation data in order to help system designers to identify relevant design choices. The approach is illustrated on an aircraft cabin design case study which concerns the simulation of different configurations of the ventilation system to study the passengers comfort in the cabin. The classification of simulation data with their corresponding comfort scores using SFCA allows to derive for each simulated input parameter the maximal interval of values which guarantee an acceptable comfort level. To evaluate the obtained results, the extracted intervals are then used as ranges of the input parameters for new simulations which confirmed the already obtained comfort levels and showed the convergence of the results.