Process Optimization of Bending SS 304L Sheets using Multi-Objective Genetic Algorithm and FEA

Waheed, Rehan; Saeed, Hasan Aftab; Butt, Sajid Ullah; Faraz, Zahid

doi:10.1109/ibcast51254.2021.9393207

Cited by 1 publication

(2 citation statements)

References 13 publications

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“…Hot rolling [8,[21][22][23] Cold rolling [24] Roller levelling [25][26][27] Stamping [28] RQ3 Stamping [29][30][31] Deep drawing [32][33][34][35][36][37][38][39][40] Bending [41][42][43] Table 2. Summary of the publication conducted in the SLR.…”

Section: Rq2mentioning

confidence: 99%

“…Lafon et al modelled different uncertainties, especially material properties to find a robust optimization procedure for a draw bending process [42]. The effect of yield strength variation and part dislocation was studied by Waheed et al to optimize bending force and residual stresses [43]. It was found that the yield strength has a major effect on bending force and residual stresses.…”

Section: Rq2mentioning

confidence: 99%

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Monitoring of fluctuating material properties for optimizing sheet-metal forming processes: a systematic literature review

ORTJOHANN

2023

Materials Research Proceedings

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Abstract. Material properties can vary both along a sheet-metal coil and from coil to coil despite tight tolerances influencing the process stability of sheet-metal processes and the part quality, which leads to rejects and machine downtime [1]. This significantly affect the economic efficiency of the process. Monitoring fluctuations in material characteristics at regular intervals along sheet-metal coils is enabled directly by non-destructive testing (NDT) before the process offering conclusions on the material properties. Another material monitoring technique arises from monitoring process conditions of the upstream processes, e.g., cold rolling, leading indirectly to insights on material properties. In this work, a systematic literature review (SLR) [2] is conducted to investigate recent approaches for material monitoring and for the utilization of resulting material data for optimizing different sheet-metal forming processes. Existing approaches for different sheet-metal forming processes are critically appraised. Based on the SLR research gaps are revealed and research opportunities, e.g., arising from a potential transfer of existing solutions between different forming processes and recent advances in data-driven methods, are identified.

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