Fixture layout can affect deformation and dimensional variation of sheet metal assemblies. Conventionally, the assembly dimensions are simulated with a quantity of finite element (FE) analyses, and fixture layout optimization needs significant user intervention and unaffordable iterations of finite element analyses. This paper therefore proposes a fully automated and efficient method of fixture layout optimization based on the combination of 3dcs simulation (for dimensional analyses) and global optimization algorithms. In this paper, two global algorithms are proposed to optimize fixture locator points, which are social radiation algorithm (SRA) and GAOT, a genetic algorithm (GA) in optimization toolbox in matlab. The flowchart of fixture design includes the following steps: (1) The locating points, the key elements of a fixture layout, are selected from a much smaller candidate pool thanks to our proposed manufacturing constraints based filtering methods and thus the computational efficiency is greatly improved. (2) The two global optimization algorithms are edited to be used to optimize fixture schemes based on matlab. (3) Since matlab macrocommands of 3dcs have been developed to calculate assembly dimensions, the optimization process is fully automated. A case study of inner hood is applied to demonstrate the proposed method. The results show that the GAOT algorithm is more suitable than SRA for generating the optimal fixture layout with excellent efficiency for engineering applications.

Wire and arc additive manufacturing (WAAM) is a competitive technique, which enables the fabrication of medium and large metallic components. However, due to the presence of coarse columnar grains in the additively manufactured parts, the resultant mechanical properties will be reduced, which limits the application of WAAM processes in the engineering fields. Grain refinement and improved mechanical properties can be achieved by introducing ultrasonic vibration. Herein, we applied ultrasonic vibration to the WAAM process and investigated the effects of wire feed speed, welding speed, and ultrasonic amplitude on the weld formation and grain size during ultrasonic vibration. Finally, a regression model between the average grain size and wire feed speed, welding speed, and ultrasonic amplitude was established. The results showed that due to the difference in heat input and cladding amount, wire feed speed, welding speed, and ultrasonic amplitude have a significant influence on the weld width and reinforcement. Excessive ultrasonic amplitude could cause the weld to crack during spreading. The average grain size increased with increasing wire feed speed and decreasing welding speed. With increasing ultrasonic amplitude, the average grain size exhibited a trend of decreasing first and then increasing. This would be helpful to manufacture parts of the required grain size in ultrasonic vibration-assisted WAAM fields.

The optimal fixture scheme can effectively reduce the deformation of sheet metal parts in the normal direction of their main plane. The fixture layout design requires a great deal of finite element analysis, which limits efficiency and quality of fixture design. This article proposes a two-stage method to decrease the number of finite element analyses for fixture layout design. First, three locating points are generated by using particle swarm optimization based on the rigid model. Second, the other points are optimized by establishing a response surface modeling based on radial basis function. Finally, through the case of rear bracket plate, this work elaborates two-stage fixture locating scheme design process. The results show that the two-stage method has good simulation effect and higher prediction accuracy.

Multi-sequence modelling is proposed to optimise assembly sequences for compliant body assemblies such as automotive and aircraft bodies. Multi-sequence modelling is composed of assembly modelling, assembly sequences, tolerance analysis, and assembly operations. Assembly modelling describes the geometric modelling through the liaison graph, which is based on assembly sequence optimisation. Assembly sequences provide information for assembly sequence optimisation. Three-dimensional tolerance analysis is employed to evaluate assembly operations, which is different from previous conceptual tolerance analysis. A genetic algorithm is presented to optimise assembly operations among components. Results show that different sequences lead to a different tolerance of key product characteristics because assembly operations among components are not identical. This paper provides the flowchart of optimising assembly sequences according to the tolerance of key product characteristics.

The distribution of contact pressure on the Membrane Electrode Assembly (MEA) significantly affects the performance of a Proton Exchange Membrane Fuel Cell (PEMFC). This paper establishes a PEM fuel cell model to investigate the impact of bolt load and its distribution, sealing gasket hardness, and size on the magnitude and distribution of contact pressure on the MEA during assembly. Thermal–mechanical coupling is employed to simulate the thermal effects resulting from chemical reactions under operational conditions. The findings reveal that there is an extremum of pressure uniformity in the range of 5000 to 6250 N for bolt loads. When the average bolt load is lower than this extremum, altering the distribution of the load can effectively enhance the uniform distribution of contact pressure. Stiffer gaskets reduce the contact pressure on the MEA while increasing the pressure on the gasket itself, resulting in reduced deformation. A rational matching relationship among gaskets, Gas Diffusion Layers (GDLs), and seal grooves is proposed. During operational conditions, thermal effects decrease the sealing performance and also impact the magnitude and distribution of contact pressure on the MEA. These outcomes provide significant guidance for the assembly and performance evaluation of PEMFCs.