Research On Production Dispatching And Management System Of Underground Mining Based On Internet Of Things At Xincheng Gold Mine

Scheduling is an important content of modern enterprise management, it is a bridge of management and liaison work, and it is the key to maintaining safe production each link group company, and it is the implementation of various economic and technical indicators of the staff, it has the organization, coordination, balance, command, supervision and usually all kinds of information collection, feedback, handling a number of functions in the enterprise safety in production process. The traditional scheduling work mainly based on drawings, mainly through the artificial management.Many distributed data management tasks, heavy, low efficiency, by experience and sensory processing problems in the production, lack of quantitative positioning, poor accuracy.Taking the production dispatching management system for Xincheng Gold Mine as a case background and utilizing the advanced Internet of Things technology and the concept of integration, this research aims to establish an improved and systematized management system which, by making full use of intelligent perception and signal transmission platform, integrates involved location system, environmental monitoring system, signals Intelligence system, voice-command system, et al.Combining the theory and feature analysis, the modern business management of mines, especially the theoretical basis and essential feature of the management for production scheduling were deeply analyzed.Considering that practice is complementary to theory, measures were taken to integrate them together by analyzing the underground mining production dispatching management system in Xincheng Gold Mine individually.This investigation verifies the feasibility and reliability of the Internet of Things.Safety of people and equipment underground as well as high-efficient mining could be ensured by introducing it into the management of production schedule of underground mining.This study could promote the implementation of intelligent mining system and could have many practical applications.