March 2021

SPECIAL FOCUS Production Engineering more sophisticated, I believe this question will become increasingly pertinent. In some respects, companies who are only now starting to move into AM have the advantage here, as they can implement a fully-integrated AM workflow – one that encompasses post- processing – from the outset. For companies who already have established AM processes, it is more of a challenge. The last thing they want to do is have to stop production and redesign systems from scratch. The onus is therefore on solution providers to create systems that are, in effect, ‘open’. Or, in other words, they can be seamlessly integrated with any system currently in use. As I previously mentioned, most AM production environments have grown organically over time to meet specific needs or challenges. As a result, the landscape is extremely fragmented – nothing is standardised and there are a lot of proprietary systems in place. To enable a swift and smooth transition to full automation, it is imperative that any post-processing solution is able to ‘plug in’ to whatever systems are in use. This means it should be compatible with all existing MES or ERP software and can also be easily integrated with external systems such as cleaning and part quality enhancing post-processing hardware. The AM ecosystem as a whole is at an exciting and pivotal point in the technology’s evolution. In order to unlock its full potential, it is crucial that companies stop thinking about post- processing in isolation – if they are even thinking about it at all – and consider how it can be implemented into a seamless end-to-end AM workflow. It is only by doing so that AM will be able to deliver on its promises off the last decade and ascend to its rightful place as a fully-digital, fully-connected part of the factory of the future. * Carlos Zwikker is CCO at AM-Flow Putting Words into action The first step to automating AM post-processing is to be able to identify each and every part as it leaves the 3D printer. As a result, machines are coming to market that are capable of identifying 3D printed parts in a split second. For example, AM-Flow’s AM- VISION identification module is fitted with ten cameras that take multiple images of a printed part as it passes through the unit, which are then cross-referenced with meta- data from its STL file. From this information, the machine can identify parts in as little as 0.2 seconds, regardless of how many parts are being printed or how they are positioned on the conveyor belt. What’s more, by harnessing the power of machine learning, the identification process can be fine-tuned over time, so that it continually becomes more accurate and reliable. The ability to identify 3D printed parts makes full track and trace capability a reality, which is another important milestone that must be achieved to bring the efficiency of AM into line with traditional manufacturing processes. Of course, once you can automatically identify a 3D printed part, you can also sort it, pick it, transport it and bag it. As a result, we are also seeing the arrival of modules to automate each of these individual processes as well, as part of a seamless, end-to-end digitalised workflow. Talking Industry CALL FOR FUTURE PANELISTS for our online panel discussions Contact us at Plant & Works Engineering for more information: *HRUJLH 7XUQHU 01732 37 1084 georgie.turner @dfamedia.co.uk | Damien Oxlee 01732 370342 damien.oxlee@dfamedia.co.uk