关键词: 产品装配, 制造成熟度, 等级评估, BP神经网络, AdaBoost算法

Abstract: In the existing manufacturing readiness level assessment of complex product assembly, the index weight and index score were evaluated by experts from experience. This resulted in some deficiencies such as subjectivity, heavy work, long time, and non-impartment of knowledge in the assessment cases. To improve the efficiency and objectivity of manufacturing readiness level assessment of complex product assembly, utilizing the dataset of manufacturing readiness level assessment cases, the manufacturing readiness level assessment was discussed herein based on BP artificial neural network and AdaBoost algorithm. A manufacturing readiness assessment index system of complex product assembly was established. The quantification of index and readiness level assessment were proposed based on fuzzy evaluation and membership function. Then the manufacturing readiness level assessment of complex product assembly was modeled based on BP neural network. The AdaBoost algorithm was applied to optimize readiness level assessment model based on BP neural network. To optimize the assessment model, it is trained on the dataset of manufacturing readiness level assessment cases and the results of BP-AdaBoost algorithm was analyzed. The optimal assessment model was obtained. Experimental results show that the assessment is good in reliability and accuracy based on BP-AdaBoost algorithm.

Key words:  , product assembly, manufacturing readiness, level assessment, BP artificial neural network, AdaBoost algorithm