•The origin and evolution of Digital Twin (DT) are reviewed, along with its implementation process. To describe the physical shop-floor more comprehensively and accurately, a five-dimensional modeling approach of Shop-floor Digital Twin (SDT), including geometry, physics, behavior, rule, and data, is proposed. ESHLEP-N model is to build the operation logic of shop-floor. Markov chain is used in the modeling of deduction rules. A shop-floor data management model is constructed to provide support for modeling in other dimensions.•Aiming at elements and processes on the physical shop-floor, a DT-based 3D visual and real-time monitoring approach and a Markov chain-based prediction approach are proposed, for monitoring and predicting shop-floor operating status based on the constructed SDT.•A DT-based visual monitoring and prediction system for shop-floor operating status, called DT-VMPS, is developed. The engineering practicability of the proposed technique is verified with a case study, which promotes the application of DT in the production stage. Digital twin (DT) technology provides a novel, feasible, and clear implementation path for the realization of smart manufacturing and cyber-physical systems (CPS). Currently, DT is applied to all stages of the product lifecycle, including design, production, and service, although its application in the production stage is not yet extensive. Shop-floor digital twin (SDT) is a digital mapping model of the corresponding physical shop-floor. How to build and apply SDT has always been challenging when applying DT technology in the production phase. To address the existing problems, this paper first reviews the origin and evolution of DT, including its application status in the production stage. Then, an implementation framework for the construction and application of SDT is proposed. Three key implementation techniques are explained in detail: the five-dimensional modeling of SDT; DT-based 3D visual and real-time monitoring of shop-floor operating status; and prediction of shop-floor operating status based on SDT using Markov chain. A DT-based visual monitoring and prediction system (DT-VMPS) for shop-floor operating status is developed, and the feasibility and effectiveness of the proposed method are demonstrated through the use of an engineering case study. Finally, a summary of the contributions of the paper is given, and future research issues are discussed.