Abstract: To prevent the overdue risks caused by randomness and dynamic events during rocket final assembly process, an early warning method for tardiness precaution is proposed to ensure in-time delivery. The method includes three steps: indicator monitoring, warning sign recognition and warning level prognostication. The inputs are quantized indicators which are elaborately designed by analyzing key factors and their mechanisms influencing the cycle time. Its main task is to monitor the progress of the rocket final assembly. An imbalanced learning algorithm considering the unbalanced nature of the data under different warning levels is utilized to achieve warning sign recognition. By considering both the tardiness of the job and the difficulty in adjustment during sample collecting, the warning level of sample is designed to realize warning level prognostication. The effectiveness and superiority of the proposed model are proven by applying the model to practical production data collected from some aerospace equipment company in Shanghai.

Key words: early waring model; tardiness precaution; rocket final assembly process; imbalanced learning