The digital twin workshop is of great significance for the design of the new workshop and the upgrading of the original workshop, but the characteristics of “human–machine–environment” dynamic and static integration bring challenges to the rapid modeling of the digital twin workshop. The existing methods have problems such as low efficiency of workshop 3D scene modeling, difficulty in realizing dynamic and static fusion modeling, and lack of quantitative evaluation of dynamic and static fusion. For the above problems, under the existing concept of digital twin workshop, combined with three-dimensional scanning technology, indoor positioning technology, sensor technology, etc., a rapid modeling method of digital twin workshop based on dynamic and static fusion of human–machine–environment is proposed, and the corresponding modeling framework is established. The rapid reconstruction of the static environment of the digital twin workshop based on three-dimensional laser scanning, the dynamic object perception of the workshop based on multi-sensor fusion, and the dynamic and static fusion driven by real-time data are studied. The evaluation index of dynamic and static fusion is designed to quantitatively evaluate the fusion effect of the constructed digital twin workshop. Finally, the robot manufacturing workshop of Zhengzhou University of Light Industry is tested to verify the feasibility and effectiveness of the proposed method.