Metals (Jan 2022)

A Review on Part Geometric Precision Improvement Strategies in Double-Sided Incremental Forming

  • Sattar Ullah,
  • Peng Xu,
  • Xiaoqiang Li,
  • Yanle Li,
  • Kai Han,
  • Dongsheng Li

DOI
https://doi.org/10.3390/met12010103
Journal volume & issue
Vol. 12, no. 1
p. 103

Abstract

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Low geometric accuracy is one of the main limitations in double-sided incremental forming (DSIF) with a rough surface finish, long forming time, and excessive sheet thinning. The lost contact between the support tool and the sheet is considered the main reason for the geometric error. Researchers presented different solutions for geometric accuracy improvement, such as toolpath compensation, adaptation, material redistribution, and heat-assisted processes. Toolpath compensations strategies improve geometric precision without adding extra tooling to the setup. It relies on formulas, simulation, and algorithm-based studies to enhance the part accuracy. Toolpath adaptation improves the part accuracy by adding additional equipment such as pneumatically or spring-loaded support tools or changing the conventional toolpath sequence such as accumulative-DSIF (ADSIF) and its variants. It also includes forming multi-region parts with various arrangements. Toolpath adaptation mostly requires experimental trial-and-error experiments to adjust parameters to obtain the desired shape with precision. Material redistribution strategies are effective for high-wall-angle parts. It is the less studied area in the geometric precision context in the DSIF. The heat-assisted process mainly concentrates on hard-to-form material. It can align itself to any toolpath compensation or adaptation strategy. This work aims to provide DSIF variants and studies, which focus on improving geometric accuracy using various methodologies. It includes a brief survey of tool force requirements for different strategies, sheet thickness variation in DSIF, and support tool role on deformation and fracture mechanism. Finally, a brief discussion and future work are suggested based on the insights from several articles.

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