摘要
Abstract
Conventional crane management is hindered by extensive yet inefficient maintenance strategies,underutilized data assets,dynamic site environments,and massive data-processing demands.To address these challenges,an intelligent mechanical-equipment management system was developed through the deep integration of Internet-of-Things sensing,big-data decision analytics,and lean-management principles.Leveraging five core functions,including real-time aggregation of multi-source heterogeneous data,intelligent assessment of equipment health,proactive early warning and intervention against latent risks,lean control of whole-life-cycle costs,and intelligent collaborative optimization of operational processes,the system enables a paradigm shift from reactive to preventive,from experience-driven to data-driven,and from fragmented to integrated management.Its feasibility has been validated through a representative field implementation.关键词
起重机械/智能管控/预测性维护/物联网Key words
hoisting machinery/intelligent control/predictive maintenance/Internet of Things分类
资源环境
