Process parameter probability model optimization method

The invention belongs to the field of intelligent manufacturing, and particularly relates to a process parameter probability model optimization method, which comprises the following steps of: generating a sample by adopting a simulation model, constructing a low-precision neural network model of whi...

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Bibliographic Details
Main Authors HU ZHENGNAN, ZENG XIANGRUI, YIN ZHOUPING
Format Patent
LanguageChinese
English
Published 20.02.2024
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:The invention belongs to the field of intelligent manufacturing, and particularly relates to a process parameter probability model optimization method, which comprises the following steps of: generating a sample by adopting a simulation model, constructing a low-precision neural network model of which the input is process parameters and the output is workpiece performance, executing parameter probability model optimization on the model, estimating an optimal solution of the model, and utilizing the optimal solution for multiple times to optimize the process parameter probability model. Performing actual production to obtain a plurality of actual workpiece performances, obtaining a plurality of workpiece performances based on the low-precision neural network model at the same time, and constructing a high-precision neural network model of which the input is the workpiece performances output by the process parameters and the low-precision neural network model and the output is the workpiece performances; and pe
Bibliography:Application Number: CN202311562314