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<p>The single point incremental forming (SPIF) process is most suitable for producing custom-made parts and prototyping. The absence of a die, as used in conventional forming, minimizes the cost and enhances the flexibility of SPIF. On the other hand, the extended processing time is the major drawback of SPIF, which is considerably mitigated in multi point incremental forming (MPIF). Also, MPIF offers improved surface finish and geometrical accuracy. This research work focuses on the MPIF process on grade 2 titanium sheets. The input factors chosen for the study are tool speed, step depth and tool feed rate. In addition, to analyze the significance of the input factors on surface roughness, forming depth, formability and forming time, response surface methodology (RSM) is used. A three-level three-factor experimental trial was selected based on the box Behnken design (BBD). The optimum parameter combinations for improved formability, surface finish, forming depth and minimum forming time are found and experimentally validated using a confirmation test. The optimum results are obtained when the forming operation is carried out at tool speed of 500&#xa0;rpm, feed rate 500&#xa0;mm/min and 0.15&#xa0;mm step depth. Predictive models for single objective and multi objective are generated using artificial neural network (ANN). The ANN models developed are capable of predicting the output with high confidence level the results are validated by additional set of experiments. Fractography analysis of formed sheet metal parts are also performed and the results shows the formation of micro voids in the sheet metal and the transformation of failure mode from void based to intercrystalline separation.</p>

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Investigation of the fracture behaviour and process parameter optimization using RSM and ANN during multi-point incremental forming of titanium grade 2 sheets

  • 期刊论文

  • 发表日期：

    2025年3月4日

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  • M. Shafeek,
  • V. N. Narayanan Namboothiri,
  • C. Raju

摘要

The single point incremental forming (SPIF) process is most suitable for producing custom-made parts and prototyping. The absence of a die, as used in conventional forming, minimizes the cost and enhances the flexibility of SPIF. On the other hand, the extended processing time is the major drawback of SPIF, which is considerably mitigated in multi point incremental forming (MPIF). Also, MPIF offers improved surface finish and geometrical accuracy. This research work focuses on the MPIF process on grade 2 titanium sheets. The input factors chosen for the study are tool speed, step depth and tool feed rate. In addition, to analyze the significance of the input factors on surface roughness, forming depth, formability and forming time, response surface methodology (RSM) is used. A three-level three-factor experimental trial was selected based on the box Behnken design (BBD). The optimum parameter combinations for improved formability, surface finish, forming depth and minimum forming time are found and experimentally validated using a confirmation test. The optimum results are obtained when the forming operation is carried out at tool speed of 500 rpm, feed rate 500 mm/min and 0.15 mm step depth. Predictive models for single objective and multi objective are generated using artificial neural network (ANN). The ANN models developed are capable of predicting the output with high confidence level the results are validated by additional set of experiments. Fractography analysis of formed sheet metal parts are also performed and the results shows the formation of micro voids in the sheet metal and the transformation of failure mode from void based to intercrystalline separation.