journal article·2018-07

Shape accuracy analysis of multi-point forming process for sheet metal under normal full constrained conditions

Bin-bin Jia, Wei-Wei Wang

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Abstract

In order to study the shape accuracy of multi-point forming (MPF) process for sheet metal under normal full constrained conditions, the in-depth analysis of shape accuracy of workpieces in multi-point forming with individually controlled force-displacement (MPF-ICFD) process is conducted in this paper by combining experiment, theoretical analysis and numerical simulation. The influences of normal force, material thickness and material properties on the shape accuracy of the feature surface are studied, and the shape accuracy characteristics of the sheet under different parameters are obtained. Afterwards, the stress and strain characteristics of sheets are obtained by numerical simulation. Finally, the effect of normal force on shape accuracy was revealed by establishing a mechanical model of the sheet metal under normal full constrained conditions. Moreover, the amount of springback reduction in MPF-ICFD is defined quantitatively. Compared with the normal unconstrained conditions, the shape accuracy of sheet metal is improved significantly under normal full constrained conditions. The stress and plastic deformation are more uniform and the amount of springback is smaller. For Q 295 steel plate with thickness of 2.0 mm, the difference between the maximum value and the minimum value of the reaction force of punch decreases from 4515.9 N to 1475 N when the forming force is 2500 N. Besides, the bending moment of the sheet on the unit width decreases from 357.9 N • mm to 328.1 N • mm. The average shape error E rr and the amount of springback Δk decreases by 60.05% and 16.03%, respectively.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Metal Forming Simulation Techniques · Laser and Thermal Forming Techniques · Metallurgy and Material Forming

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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