Session: SYMP 4-8: Shape Memory Alloy Applications

Paper Number: 140067

140067 - Optimizing Force Distribution in Deep Drawing Tools Using Sma High Load Actuators 

This paper presents and realizes a novel approach to manipulate the force distribution in deep drawing tools using high load SMA actuators. Deep drawing is a basic metal forming technology used to form flat sheet metal into complex, three-dimensional shapes such as cups, cans, or automotive components with precision and efficiency. Therefore, it is widely used in industries such as automotive, aerospace and consumer goods. In the process, a blank sheet is first secured at its edges and then gradually drawn into a die cavity by a descending punch. As the punch advances, the metal stretches and conforms to take the shape defined by the die. The success of deep drawing depends on the careful control of various parameters, including material thickness, lubrication, tool design, tool wear and process conditions, all of which are designed to prevent reject parts.

Introducing a new deep drawing tool, or transferring existing tools to alternative presses, typically involves a complex, time-consuming, and costly process to seamlessly integrate them into the production line. Due to the current lack of automation in these processes, well-trained specialists with extensive experience remain indispensable for the fine adjustment of the force distribution in deep drawing tools. However, there is a growing scarcity of specialist due to the demographic change in many countries. This not only increases the cost pressure on deep drawing operations, but also the risk of this technology. In addition, the ever-increasing demands on the process, driven by more complex part geometries and novel semi-finished materials, are pushing deep drawing processes to the limits of their stability. As a result, even small process variations, e.g. due to variations in component quality or environmental conditions, often result in reject parts during production. For these reasons, it is necessary to automate the fine adjustment of deep drawing tools, or more precisely, their force distribution. This can only be achieved with multiple actuators, which introduce different micro-deformations into the tool and change the stiffness distribution.

High load actuators based on thermal shape memory alloys (SMAs) are ideal for this task. Unlike competing technologies, they offer a small installation space, sufficient forces, low costs, and a simple control. Therefore, they offer a significant potential for influencing the tool-dependent force distribution, sheet retention forces and associated sheet feed rates. The distribution of sheet feed rates has a significant impact on the adherence of the deep drawing process to the process window. SMA high load actuators can both statically optimize the press force distribution during fine adjustment processes, minimizing costs and time, and on the other hand dynamically compensate for fluctuating process parameters (such as sheet thickness, lubrication, or tool wear) from stroke to stroke, effectively preventing the production of reject parts.

The approach investigated in this paper is the integration of high load SMA actuators into the blank holder to create an adaptive pressure pad. In the case of this study, an array of sixteen high-load SMA actuators was integrated into the blank holder. Each actuator is capable of exerting forces of up to 5 kN and deformations up to 180 µm. Experimental investigations validate the potential of SMA actuators to adjust the force distribution, both quasi-statically and from stroke to stroke. The aim is to reduce the influence of process variations and speed up fine adjustment processes.

Presenting Author: Andreas Hofer Fraunhofer Institute for Machine Tools and Forming Technology IWU

Presenting Author Biography: Andreas Hofer graduated from the Technical University of Dresden, Germany, in 2022 with a degree in mechatronics. Since 2023 he works as a research associate at the Fraunhofer Institute for Machine Tools and Forming Technology IWU, Dresden, Germany, in the field of shape memory technologies.
His current research interests include the research and development of high load SMA actuators and adaptive connector systems based on SMAs.

Authors:

Andreas Hofer
Kai Thüsing
Kenny Pagel
Lucas Hamm
Christian Weck
Welf-Guntram Drossel