热力透平2025，Vol.54Issue(2)：97-100,4.DOI:10.13707/j.cnki.31-1922/th.2025.02.004
基于数据驱动的透平叶片加工工时预测研究
Estimation on Processing Labor Hours of Turbine Blade Based on Data-Driven Technology
宫同浩 1赵蓉 1曹雪华1
作者信息
- 1. 上海汽轮机厂有限公司,上海 200240
- 折叠
摘要
Abstract
Due to the complexity of manufacturing process and the volatility of market demand of turbine blade,the advanced planning and scheduling(APS)system is needed in enterprises,and complete basic data is crucial for the system.Aimed at the problem of labor hours data missing of new turbine blades in planning and scheduling,a data-driven estimation method is proposed.This method utilizes a dual-layer solution based on machine learning to solve the problems of device selection and processing labor hours estimation,and can provide data support for the APS system to help refined management and digital transformation of enterprises.The research results can provide reference for intelligence development of large-scale discrete manufacturing industries and implementing data-driven decision-making approaches.关键词
汽轮机叶片/高级智能排程/数据驱动/数字化转型/智能制造Key words
turbine blades/advanced planning and scheduling(APS)/data-driven technology/digital transformation/intelligent manufacturing分类
能源与动力引用本文复制引用
宫同浩,赵蓉,曹雪华..基于数据驱动的透平叶片加工工时预测研究[J].热力透平,2025,54(2):97-100,4.
