Last month, we looked closely at the role of automation in the additive manufacturing industry and at how it is the key to advancing the technology’s broad industrialization. One of the areas in the AM chain where automation is still considered to be lacking is in metal post-processing. Recognizing this, UK-based metal AM company Renishaw teamed up with startup Additive Automations to increase the degree of automation across metal AM post-processing.
The joint project, called Separation of Additive-Layer Supports by Automation (SALSA), seeks to integrate cutting edge collaborative robots (cobots) to automate the support removal process. The partners say their work has the potential to reduce the average cost per part by 25%, which could make metal AM more viable for large volume production.
The companies have actually been working together since last year, with Renishaw providing its in depth knowledge of metal AM to Additive Automations, a Sheffield-based startup specializing in robotic systems for 3D printing. The young firm, which is backed by Innovate UK and the National Research Council of Canada, has also been working with the University of Sheffield Advanced Manufacturing Research Centre (AMRC).
As part of SALSA, Renishaw presented Additive Automations with four AM build examples, designed for the medical, oil and gas, automotive and mechanical engineering sectors. These parts underwent Additive Automations’ cobot-powered support removal to demonstrate the viability of the technique for various industrial applications. Ultimately, the partners aim to use robotics and deep learning to digitalize AM finishing processes, which are still largely manual.
“Automating support removal and finishing in AM completely changes the economics when scaling up AM, and for the first time makes it feasible for manufacturers around the world to adopt this technology in rapid production,” said Robert Bush, Founder and CEO of Additive Automations. “The digitalisation of AM also comes with an increase in quality, traceability and repeatability. Given that on average almost two thirds of post-processing costs are from finishing and support structure removal, we believe automation can reduce costs by an average of 25% per part.”
The automated AM post-process being evaluated in the joint SALSA project involves the use of cobots because of their high payload-to-size ratio and integrated force sensors, which gather data about the geometry of the printed part. This data is then analyzed using digital twin technology, which enables the cobot to recognize where support structures are placed. The metal supports can then be precisely removed using an end-effector tool. The end-effector tool is also worth talking about: Additive Automations has developed a workflow for producing robotic end-effectors using generative design and additive manufacturing. A detailed case study reveals how the young company worked with Renishaw Canada, AMRC and Autodesk to pioneer this workflow.
Bryan Austin, Director of AM Sales at Renishaw, believes the collaboration could accelerate the adoption of metal AM in various sectors. He said: “Improvements in post-processing could bring AM to the forefront of new applications in medical and aerospace applications. An automated manufacturing process could make AM adoption more appealing to manufacturers operating large volume production lines.”