Modeling and Optimization of Job Assembly Rescheduling Problem Based on Job Quality Prediction Mechanism

Abstract:

Repair jobs resulting from poor assembly quality of jobs in the aircraft assembly process can disturb assembly scheduling plans and cause economic losses. This paper proposes a prediction-rescheduling closed-loop framework in order to solve this scheduling problem. In the front part of this framework, job quality prediction models are trained using historical data of quality-related components in deteriorations and quality characteristic deviations of jobs. Based on the prediction results of jobs, a rescheduling model is established in the later part of this framework and an improved-immune-algorithm (I-I-A) is designed to generate a new scheduling plan for the assembly line. The effectiveness of the I-I-A is verified from different aspects and the advantages and disadvantages of the performance of the closed-loop framework suggested in this paper is analyzed in comparison with other frameworks.