Joints are commonly used in many large-scale engineering systems to ease assembly, and ensure structural integrity and effective load transmission. Most joints are designed around friction interfaces, which can transmit large static forces, but tend to introduce stick-slip transition during vibrations, leading to a nonlinear dynamic system. Tools for the complex numerical prediction of such nonlinear systems are available today, but their use for large-scale applications is regularly prevented by high computational cost. To address this issue, a novel adaptive reduced-order model (ROM) has recently been developed, significantly decreasing the computational time for such high fidelity simulations. Although highly effective, significant improvements to the proposed approach is presented and demonstrated in this paper, further increasing the efficiency of the ROM. An energy-based error estimator was developed and integrated into the nonlinear spectral analysis, leading to a significantly higher computational speed by removing insignificant static modes from the stuck contact nodes in the original reduced basis, and improving the computational accuracy by eliminating numerical noise. The effectiveness of the new approach was shown on an industrial-scale fan blades system with a dovetail joints, showing that the improved adaptive method can be 2–3 times more computationally efficient than the original adaptive method especially at high excitation levels but also effectively improve the accuracy of the original method.