Abstract: This paper proposes the concept, architecture and construction methods of the digital twin smart mining workface system (DTSMW) in order to further improve the autonomous operation and human-machine interaction ca- pability of intelligent coal mining workface system,and achieve the true state of unmanned mining. The fusion applica- tion of 5G communication technology,internet of things technology and bionic intelligence technology is also intro- duced,which is much helpful for building a digital twin remote operating platform of smart mining workface. The digital twin smart mining workface is firstly defined as a three-dimensional mirror scenario of coal mining process with data vi- sualization,human-machine interaction and process optimization. The new DTSMW system consists of three parts as physical workface,digital workface and data transmission. The key technologies in the DTSMW system include physical workface,virtual workface, twin data, information interaction, model driver, edge computing, immersive experience, cloud service,information physics system, intelligent equipment, etc. The DTSMW system could achieve the digital twins of mining model,mining process,equipment performance,production management and safety monitoring,which will improve the mining process simulation,optimization and monitoring capabilities. In the paper,the bionic intelli- gence characteristics of the smart mining workface are described,and the basic intelligence characteristics of physical module (torso),information module ( brain),communication module ( nerve),control module ( brain muscle),twin module (image) are discussed. Especially,the bionic intelligence features of the shearer,hydraulic support and scrap- er conveyor are described in detail. The complex information data of smart mining workface are summarized into three flows to correlate the interaction state from environmental,control and energy in the coal mining process. The environ- mental data flow and control data flow come from the input information and the adaptive control information to the coal cutting,hydraulic support and coal flow transport unit. The energy information flow comes from the energy exchange state in mining equipment corresponding to coal seam and roof pressure variations. In view of the huge amount of data flow in the DTSMW system,the digital thread method is proposed for data management,dividing the data flow into pe- riodic data,random data and sudden data for accurate modeling and processing,to ensure the stable data-driven of the DTSMW system. Through a comparative analysis,it is recognized that the DTSMW system could improve the intelli- gence of the existing remote control center in underground coal mining workface,and provide a new monitoring system architecture for the future unmanned operation of higher level smart mining workface.