Iterative learning control of single point incremental sheet forming process using digital image correlation

Abstract

Abstract Single Point Incremental Sheet Forming (SPIF) is a versatile forming process that has gained significant traction over the past few decades. Its increased formability, quick part adaption, and reduced set-up costs make it an economical choice for small batch and rapid prototype forming applications when compared to traditional stamping processes. However, a common problem with the SPIF process is its tendency to produce high geometric error due to the lack of supporting dies and molds. While geometric error has been a primary focus of recent research, it is still significantly larger for SPIF than traditional forming processes. In this paper, the convergence behavior and the ability to reduce geometric error using a simple Iterative Learning Control (ILC) algorithm is studied with two different forming methods. For both methods a tool path for the desired reference geometry is generated and a part is formed. A Digital Image Correlation (DIC) system takes a measurement and the geometric error along the tool path is calculated. The ILC algorithm then uses the geometric error to alter the tool path for the next forming iteration. The first method, the Single Sheet Forming (SSF) method, performs each iteration on the same sheet. The second method, the Multi Sheet Forming (MSF) method, performs each iteration on a newly replaced sheet. Multiple experiments proved the capability of each method at reducing geometric error. It was concluded that using the MSF method allows for negative corrections to the forming part and, therefore, leads to better final part accuracy. However, this method is less cost effective and more time consuming than using the standard SSF methodology. In addition, it was found that in order to effectively correct a part with an ILC algorithm, steps must be taken to increase the controllability of the part geometry.