Assembly Sequence Planning (ASP) is a critical stage in product development that strongly influences manufacturing performance. However, communication gaps between product designers and system engineers often lead to suboptimal assembly plans, as Computer-Aided Design (CAD)–based proposals may not fully align with Model-Based Systems Engineering (MBSE) requirements. To address this challenge, this study proposes a collaborative CAD–MBSE assembly planning optimization methodology that integrates both domains within a unified decision-making framework. This approach enables bidirectional information exchange between designers and system engineers, allowing geometric feasibility and system-level constraints to be jointly considered during assembly sequence generation. Furthermore, a multi-objective optimization process based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to balance multiple assemblability indicators, enabling the identification of requirement-compliant assembly sequences. The effectiveness of the methodology is demonstrated through a vibration generator case study, which shows improved coordination between design and system models, enhanced assembly quality, and a reduction in the number of candidate sequences while maintaining compliance with design requirements. These results highlight the value of multi-criteria evaluation and collaborative decision-making in achieving efficient and consistent assembly planning outcomes.
