Rivelin bridges human creativity with machine accuracy to teach metalworking robots to do the jobs people don't want to.
slide 4 to 6 of 6
Digital & Sustainable Manufacturing
Scaling near-net-shape manufacturing is tough
Quality issues, uncompetitive costs and unfilled jobs have prevented companies from using technologies like additive manufacturing and casting on their production lines; but manufacturers know they must break from the past in order to build for the future. The question then, is how do you overcome these barriers?
Post-processing is a necessary element to near-net-shape manufacturing but it's skilled, noisy, dusty and strenuous work. Those with the necessary skills are approaching retirement age and the younger generation isn't willing to replace them.
The toughest job in post-processing is metalworking. It takes decades of training and dedication to achieve accuracies of 200 microns or better. Naturally there are variations between metalworkers and this risk is complex and costly to manage at production scales.
The business case for near-net-shape manufacturing versus subtractive manufacturing is often on a knife edge. Post-processing commonly costs more than the manufacturing process itself. This is because of manual and time consuming processes like support removal, gate and runner removal, deflashing, deburring, depowdering, witness removal, finishing, polishing and inspection.
Near-net-shape manufacturing is one of the technologies that can help us achieve a net-zero carbon economy. However focus needs to be put on reducing the scrap rate and energy wastage in post-processing. More must be done to repair and refurbish components.
An Intelligent Automation Platform
Our patent pending technology centers around the integration of cutting edge hardware with intelligent control software. Capable of processing metallic, polymer and composite parts in a wide range of sizes, it's also cross-compatible with different robot vendors such as Yaskawa and ABB.