Wall Thickness Distribution Of Parts Research Articles

The role of process parameters in determining wall thickness distribution in plug‐assisted thermoforming

AbstractThis article describes the results of a comprehensive investigation to determine the link between process parameters and observed wall thickness output for the plug‐assisted thermoforming process. The overall objective of the work was to systematically investigate the process parameters that may be adjusted during production to control the wall thickness distribution of parts manufactured by plug‐assisted thermoforming. The parameters investigated were the sheet temperature, plug temperature, plug speed, plug displacement, plug shape, and air pressure. As well as quantifying the effects of each parameter on the wall thickness distribution, a further aim of the work was to improve the understanding of the physical mechanisms of deformation of the sheet during the different stages of the process. The process parameters shown to have the greatest effect on experimentally determined wall thickness distribution were the plug displacement, sheet temperature, plug temperature, and plug shape. It is proposed that during the plug‐assisted thermoforming of polystyrene the temperature dependent friction between the plug and sheet surface was the most important factor in determining product wall thickness distribution, whereas heat transfer was shown to play a less important role. POLYM. ENG. SCI., 50:1923–1934, 2010. © 2010 Society of Plastics Engineers

Optimizing parison thickness for extrusion blow molding by hybrid method

A hybrid method consisting of finite element method (FEM), artificial neural network (ANN), and genetic algorithm (GA) was used to find the optimal parison thickness distribution for a blow molded part with required thickness distribution. Firstly, numerical simulations on the parison inflation were performed using FEM and the K-BKZ integral type constitutive equation. Based on the simulation results, a back propagation (BP) ANN model was then developed to build the relationship between parison thickness distribution and the objective function, which was used to evaluate the wall thickness distribution of part. The predictive ability of the ANN model was verified through FEM simulation results different from those utilized in the training stage. Finally, a GA was developed and used to search for the optimal parison thickness distribution. The results showed that the hybrid method proposed in this work can effectively obtain the optimal parison thickness distribution for a blow molded part with required wall thickness distribution. Compared with the trial and error method, the hybrid method can shorten the part development time and save a lot of material.

A preform design method for sheet superplastic bulging with finite element modeling

Superplastic bulging is the most successful application of superplastic forming (SPF) in industry, but the non-uniform wall thickness distribution of parts formed by it is a common technical problem yet to be overcome. Based on a rigid–viscoplastic finite element program developed by the authors, for simulation of the sheet superplastic forming process combined with the prediction of microstructure variations (such as grain growth and cavity growth), a simple and efficient preform design method is proposed and applied to the design of preform mould for manufacturing parts with uniform wall thickness. Examples of formed parts are presented here to demonstrate that the technology can be used to improve the uniformity of wall thickness to meet practical requirements.