Renishaw Joins Project To Automate Additive Manufacturing Post-Processing
Renishaw Joins Project To Automate Additive Manufacturing Post-Processing
Renishaw is collaborating with UK start-up business Additive Automations, as part of a project to automate metal additive manufacturing (AM) post-processing, which involves using collaborative robots (cobots) to perform support structure removal. The project could reduce the average cost per part by 25 percent, furthering AM’s potential as a cost-effective option for large volume production lines.
Renishaw provided four examples of AM builds, so the start-up could demonstrate its support structure removal system. The four AM parts were designed for medical, oil and gas, automotive and mechanical engineering applications.
The project, named Separation of Additive-Layer Supports by Automation (SALSA), aims to use robotics and deep learning to digitalise some of the few remaining manual processes left in AM. Cobots were chosen for their high payload-to-size ratio and integrated force sensors, which collect data to determine the geometry of AM parts. Software then analyses the data, using digital twin technology. The output is then used to determine where the support structures are so that they can be removed using an end-effector tool.
“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,” explained Robert Bush. “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 cent per part.”
“Improvements in post-processing could bring AM to the forefront of new applications in medical and aerospace applications,” explained Bryan Austin, Director of AM Sales at Renishaw. “An automated manufacturing process could make AM adoption more appealing to manufacturers operating large volume production lines.”
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