Design of sheet metal components and press tools demands a high level of knowledge and industrial experience on the part of designers. Recently, various artificial intelligence ({AI}) techniques are being used in sheet metal work to reduce complexity; minimize the dependency on human expertise and time taken in design of parts and dies as well as to improve the design efficiency. Artificial neural network ({ANN}) technique is one of the most powerful tools for solving engineering design problems and minimizing errors in experimental data. This paper describes a comprehensive review of applications of {ANN} technique to sheet metal work. Major published research work in the domain area is summarized in tabular form. Based on the critical review of available literature, further research scope is identified. The present literature review reveals that there is stern need to apply {ANN} technique to press tool design and to predict tool life in sheet metal industries.
CITATION STYLE
Kashid, S., & Kumar, S. (2013). Applications of Artificial Neural Network to Sheet Metal Work - A Review. American Journal of Intelligent Systems, 2(7), 168–176. https://doi.org/10.5923/j.ajis.20120207.03
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