# Optimized Design of Flexible Quick-Change System Based on Genetic Algorithm and Monte Carlo Method
## 4 Conclusions  
In this paper, aiming at the problems of difficult reassembly and low efficiency of large thin-walled cylindrical structural parts in the aerospace manufacturing industry, a design method of genetic algorithm and Monte Carlo method is proposed, and a high-precision and high-quality flexible quick-change process system with excellent performance is designed and developed, which is suitable for multiple varieties and multiple processes. The feasibility of the design research for the flexible quick-change process system is proved through finite element simulation and functional verification experiments:  
1. The flexible quick-change process system is capable of quickly clamping off-line, moving machined pieces, and aligning them. In contrast to the flexible quick-change process system, which uses zero point clamping technology, each changeover only takes 2 min. This significantly reduces machine downtime by 79% and boosts changeover efficiency by 53%, ultimately increasing machining efficiency. Most importantly, the system provides a high level of repetitive positioning accuracy (0.0041-0.0081 mm);
2. The maximum shear force, torsion force, and overturning force that the flexible quick-change system can withstand are the vectorial combinations of the forces on each zero point clamping unit, and they all increase with the increase in the distribution number of zero point clamping units. However, with the same number of positioning units, the repeated positioning accuracy will increase with the increase in distance between the two zero point clamping units, and the applied force and the average strain of the system will be slightly changed. The \"dot matrix\" zero layout structure is determined through genetic algorithm optimization (four positioning units are squarely distributed in the outer circle and located in the position of the radius of the outer circle, which is 537.67 mm, and three positioning units are regular triangles distributed in the inner circle). By using the optimization algorithm, blind design based on experience can be avoided, and the flexible quick-change system can bear a greater load and have high positioning accuracy;
3. The Monte Carlo method was used to analyze the influence of system load and extreme working conditions on six components of workpiece pose deviation in the process of lifting transposition, and it was concluded that the displacement deviation and rotation angle deviation obeyed normal distribution within a certain range. However, each error source has a different sensitivity to the overall pose error of the workpiece. By optimizing the Z-axis flatness with a greater error sensitivity of 0.01 mm, the repetitive positioning accuracy of the system is controlled within 0.01 mm.  
Methodology, writing--review and editing, conceptualization, H.Z.; investigation, validation, Y.Z.; supervision, funding acquisition, C.L. and H.Z.; visualization, project administration, G.W. and Z.Z.; writing--original draft, formal analysis, data curation, J.W. and Y.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Foundation of Equipment Pre-Research Area, grant number 80923010401; the Research Project Supported by Shanxi Scholarship Council of China, grant numbers 2021109 and 2021118; the Fund Program for the Scientific Activities of Selected Returned Overseas Professionals in Shanxi Province, grant number 20210040; the key core technology and generic technology research of Shanxi, grant number 2020 XX005; and the National Natural Science Foundation of China, grant number 52075503.  
Not applicable.  
The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author.  
The authors declare no conflict of interest.