Research on Data Driven Intelligent Distribution Method of Transformer Production Materials
Under the background of the informatization,digitalization and intelligence transformation of the traditional transformer discrete assembly workshop,the efficient and intelligent distribution of production ma-terials is an urgent problem to be solved.In this paper,an intelligent distribution method of production materi-als with two stages of material preparation and path decision is proposed.The material distribution task is di-vided into production material preparation stage and production material path self-decision stage.In the pro-duction material preparation stage,a prediction model of transformer production material preparation time based on Adam optimized LSTM recurrent neural network is proposed.The LSTM recurrent neural network model optimized by Adam is trained by using the time series data related to production materials,and the pre-diction of production material demand time in the next stage is accurately and reliably realized.In the self-de-cision stage of production material distribution path,the improved A∗algorithm with five-point cubic method is used to generate a distribution path with smooth path and less turning.Finally,taking a transformer discrete manufacturing workshop as an object,the intelligent distribution method of production materials is verified.
data drivenLSTM recurrent neural networkimproved A∗ algorithm
NETL
NSTL
万方数据
