Metal spinning is classified as an incremental sheet metal forming processand as such features some unique advantages over conventional stampingoperations. Their elevated number of degrees of freedom provides greatflexibility on one hand, but is cumbersome to translate into standardizedprocedures on the other. Thus the design of the process layout is a challeng-ing task, which is usually carried out manually by experienced personnel,based on a trial-and-error approach.FEM and meta-modelling are widely used state of the art methodologiesfor process analysis and optimization, but the application of these on metalspinning is very limited. Due to its highly dynamic and localised formingcharacter, accurate modelling of the process relies on full scale 3D models.In combination with the comparably long process cycles, this mostly resultsin restrictive computational times, making classical virtual optimization in-feasible.This works aims to discover systematic methodologies, which enable auto-mated tool path design for metal spinning processes. In order to do this,the finite element method is employed and optimized in terms of compu-tational time and resources. Based on the models, extensive insight onthe deformation characteristics and the failure modes is provided. Subse-quently, different concepts for automated tool path design are proposed.These are a closed loop control system, which is integrated into the mod-els, enabling constrained and failure free tool path design, and a simplifiedmodel, which approximates the results of the adaptive control strategy, butis not bound to any computational effort.The functionality of the concepts for automated tool path design is veri-fied on two different test geometries and materials. For proof of conceptthe results are validated with metal spinning tests, in which the computedpaths have been applied via CNC machine, demonstrating that the devel-oped methodologies indeed enable failure free production of components. Adetailed comparison shows that these generally surpass the manual designin aspect of quality and cycle time.
|Award date||16 May 2018|
|Publication status||Published - 2018|