Application of Artificial Intelligence in Incremental Sheet Metal Forming: A Review

Abstract

Artificial Intelligence (AI) has been widely used in manufacturing, healthcare, sports, finance, and other areas to model nonlinearities and make reliable predictions. In manufacturing, AI has been applied to improve processes, reduce costs, and increase reliability. A novel manufacturing process that has been augmented with AI is Incremental Sheet Forming (ISF), a technology that applies a step-by-step incremental feed to a sheet metal or polymer blank using a CNC machine. The quality of the produced part is affected by parameters related to four process elements: the blank, the blank holder, the forming tool, and the CNC machine (applied force). The ISF process is greatly affected by forming process parameters, material property parameters, and geometric parameters. Numerous research efforts have correlated the relationship between the ISF parameters to final product attributes using analytical, experimental, and numerical techniques. However, these techniques are not efficient due to the nonlinearities and complexities of the relationships, the time-consuming nature of the process, and extensive computational time needed to simulate the process. To compensate for these shortcomings, researchers have started to apply AI techniques in analysis of ISF. The aim of this paper is to review the application of AI in the ISF process in forming of metal sheets in order to summarize the contributions of prior research efforts and identify potential opportunities for future research.