## 6 Discussion  
Compared with existing methods, the contribution of the assembly error modeling method proposed in this paper is that introduces the impact of gravity on the truss rod and hinge's clearance into the model. The relationship between assembly error and service performance is established. Previous methods for reducing the impact of gravity include various advanced gravity compensation technologies. However, they are almost completely unable to unload the gravity of all the LSDM's components for a long time. The proposed method considers the gravity changes between ground assembly and service in space on the premise of gravity compensation. Compared with previous methods, it further reduces the impact of gravity during assembly on service performance. The verification results presented in Figure 16 show that the proposed method can improve the pointing accuracy from 0.068\({}^{\circ}\) to 0.045\({}^{\circ}\).  
In addition, the dynamic tolerance allocation based on as-built data proposed in this paper is different from the previous method, which is completed before starting the assembly task and remains unchanged during the whole assembly process. To ensure the final quality, a limit situation is considered in the previous method, i.e., the final quality should be guaranteed even if the assembly error of each process reaches the tolerance boundary. However, in the actual assembly process, the error of each process does not usually reach the boundary but is better than it in most cases. Therefore, the as-built data measured during assembly has considerable value in tolerance allocation. The proposed  
Figure 19: Assembly costs of different methods.  
method uses the as-built data as the input to dynamically allocate the tolerance of each process, which can relax tolerance while guaranteeing assembly quality. Thus, it can reduce assembly difficulty and cost. A comparison of the assembly costs is shown in Figure 19. Compared with the previous method, the dynamic tolerance allocation method reduces the LSMD assembly cost from CNY 547,232 to CNY 473,380. Moreover, if the as-built data exceed the tolerance, it can be used to evaluate whether the current process should be reworked or the subsequent processes' tolerances should be tightened to ensure the final quality in service performance.  
However, there are some limitations in this proposed method. For the assembly error model, only gravity's impact is considered; even though it is the most important factor affecting the LSDM's service performance, some other factors that have differences between ground assembly and service in space, such as temperature, radiation, and air pressure, are not yet considered in this method. Introducing those factors into the assembly error model, which could be studied in the future, may improve the proposed method and make the predicted pointing accuracy more accurate. Additionally, only GA is used for tolerance optimization in the dynamic tolerance allocation method. Besides GA, there are some other metaheuristic algorithms that could be used in the proposed method. Although it has achieved good results in reducing assembly difficulty and cost with the help of GA, this paper does not compare the effectiveness using different optimization algorithms. In the future, different optimization algorithms can be used to the proposed method, which may improve the LSDM assembly performance.