Aiming at the problem of project duration extension caused by chain rework due to functional inspection in large industrial components assembly process， a complex assembly process scheduling problem optimization model considering functional fault rework is established， and an integer programming model is established with the objective function of minimizing project duration expectation. Based on the support vector machine quality defect probability prediction model and bayesian network， the mapping relationship between personnel allocation decision and posterior rework probability is established. A hierarchic genetic tabu search algorithm （HGA-TS） is designed. The upper layer optimizes the job execution sequence based on the job list topology sequence， the lower layer optimizes the personnel allocation based on random key， and then converts it into resource stream coding local search optimization to generate proactive scheduling plan. The experimental results of the model show that giving priority to high-level resources for assembly jobs with high posterior probability can reduce the probability of functional fault rework. The algorithm comparison experiment proves the effectiveness of HGA-TS in solving this problem.