Application of Intelligence in Equipment Management
This study explores the multifaceted applications of intelligence in equipment management with the core objective of enhancing management efficiency and ensuring equipment reliability.Three key technological approaches are employed:first,a data-driven decision-making system utilizes real-time monitoring and data analysis to offer accurate decision support for equipment management;second,remote monitoring and fault alerts are realized through sensors and network technology,facilitating real-time status tracking and prompt identification and handling of potential issues;third,automated maintenance and fault diagnosis are carried out using sensor data and machine learning algorithms,significantly improving operational efficiency and reducing downtime.Additionally,this research designs an intelligent monitoring scheme for mechanical equipment,capable of precisely predicting equipment performance and residual useful life.
NETL
NSTL
万方数据
维普
