## 1 Introduction  
As the global concept of Industry 4.0 continues to mature, the needs of injection molding machine users have gradually evolved from stand-alone machines to equipment automation, networking, and intelligent machines through virtual and real system integration, allowing users to have more sophisticated operational planning and effective resources distribution. This paper demonstrates the integration of the parameter-based method of machine response in simulation analysis and the material compressibility effect of molten polymer plastics. Users will be able to determine the dynamic behavior of the material more realistically when it enters the mold cavity by obtaining more accurate results from the injection pressure simulation. Through this integration method, material waste in the mold trial process will be reduced, along with a reduction of challenges faced by front-line engineers in during real process operations. In 2014, [PERSON] et al. [1] mentioned the gravity force entering point improved filling of the cavity for the same forming time and injection pressure. The response speed of this control loop upgraded the stability of the cavity filling. In-line screws were designed and produced for use in injection molding machines in 1956. Along with the continuous development of new plastic materials and molding methods, screw development in recent years has been more focused on discharge volume, mixing, and homogenization. In terms of mixing, it is especially important to be able to obtain a homogeneous melt at a lower temperature level. For general plastic materials, the screw design requirement is high throughput. In the screw flow field virtual analysis, as the molten plastic is not a Newtonian fluid, due to the coexistence of both solid and liquid phases, the entire plasticization process becomes extremely complicated. There are various difficulties in establishing virtual calculation formulas for various screw designs; therefore, we tried to obtain the unprocessed design parameter values through VM methods and recognizable performance evaluation (RPE), and then used systematic and efficient experimental methods to identify the best parameter combination. VM technology has been developed over many years, whereby all of the elements in the injection molding process are converted into virtual quantifiable values. In 2012, [PERSON] et al. defined [2] Virtual Metrology (VM) as a method to conjecture the manufacturing quality of a process tool based on data sensed from the process tool and without physical metrology operations. In addition, in 2016, [PERSON] et al. [3] mentioned VM as a method to conjecture manufacturing quality of a process tool based on data sensed from the process tool and without physical metrology operation. In other words, VM can convert sampling inspections with metrology delay into real-time and on-line total inspection. After the calculations of the product quality and the production efficiency are completed in the virtual system, they are reflected in the physical space as recommendations for further production. In the comparison between practical injection molding and simulation analysis, the most critical implementation step is to ensure that the input data of simulation analysis is consistent with the conditions of the real-world injection processes as much as possible. However, there are many factors that can potentially cause inconsistency in subsequent comparisons, such as: the performance of the machine in terms of faster or slower mechanical response time; the characteristics in the material processing process; the data measurement method; and the geometric consistency of the product. After ensuring the correctness of these input data, the predicted results of VM are often highly consistent with the actual results and can provide users with complete calculation data in the mold cavity to facilitate the optimization and adjustment of subsequent design changes.