Dutch 3D printing post-processing and automation company AM-Flow has announced that it has raised $4 million in Series A funding.
The investment was led by BOM Brabant Ventures and supported by Materialise, Midwest Prototyping and Innovatiefonds Noord-Holland, as well as return investors Miller Turner and DOEN Participaties. AM-Flow plans to use the additional funding to build on its suite of AI-based robotics solutions, bring its technologies to new markets and provide a “step-change” in 3D printing automation.
“We are delighted to welcome our new investors, and I would like to thank our existing shareholders for their continued support,” said Stefan Rink, CEO of AM-Flow. “This strong syndicate of high-tech investors validates our approach, and the funding enables us to expand our solution portfolio and market presence.”
AM-Flow’s 3D printing automation technology
Founded in 2018, AM-Flow has bases in the Dutch cities of Amsterdam and Eindhoven, from which it provides 3D printing post-processing and factory automation services. Through its portfolio of AI-driven technologies, the company aims to allow 3D printing to “achieve its full potential,” and become cost-competitive with conventional manufacturing processes.
AM-Flow offers a combination of additive manufacturing hardware and MES software products, through which it aims to provide clients with an “end-to-end” automated production line. At present, the firm’s lineup includes AM-VISION shape recognition software, AM-SORT conveyor belt hardware and AM-EXPERT support, amongst various other services.
Leveraging its expertise in advanced 3D shape identification, machine vision and artificial intelligence technologies, the company has sought to expand the application of its services in recent years. 3D printing services provider Oceanz for instance, announced a partnership with AM-Flow to develop a series of fully-automated AM production lines in March 2020.
Implementing AM-Flow’s AI-driven software allowed Oceanz to automate a number of post-processing steps, and cut back on the time it spent on the analogue manual process. Now, having gained the backing of several established 3D printing firms and investors, AM-Flow is seeking to grow its share within international markets outside of its native Netherlands.
Industry 4.0 and AM-Flow
According to AM-Flow, optimizing 3D printing production lines is extremely challenging, as they need to be able to process parts with an almost unlimited number of possible geometries. Object identification, sorting, quality control, handling, transportation and packaging all need to be taken into account, and that’s why the firm offers its modular, machine learning tools.
The potential cost and efficiency savings of AM-Flow’s automation services has led serial investors such as BOM Brabant, and 3D printing software firm Materialise, to invest in their future development.
“Scaling additive manufacturing is not just dependent on continued innovation, but on whether we’ll be able to handle the high variety of printed components in a cost-efficient way,” said Bart Van der Schueren, CTO of Materialise. “That’s why we are excited by AM-Flow’s product portfolio, which creates a path towards cost-efficient scaling of the handling process”.
AM-Flow plans to use its newly-acquired funding to build on its current offering of AI-based robotics, and increase the speed of the 3D printing manufacturing process for its clients. Given the supply chain disruption caused by the COVID-19 pandemic, the firm also believes that now is the ideal time for companies to embrace localized production.
In order to make on-demand manufacturing work for their businesses, AM-Flow’s potential customers will need to keep their labor costs down, while limiting offshoring at any opportunity. AM-Flow has stated that the best way for manufacturers to achieve this, and optimize their overall workflow, is through full end-to-end automation of the production process.
It’s on this basis that the company offers its computer vision-based robotics solutions, and leveraging its new funding, it intends to expand their reach into new markets. AM-Flow also has grander ambitions to play its part in the introduction of industry 4.0, and views its expansion as a step towards “lights-out” fully-automated factories of the future.
“AM-Flow plays an important role in building the additive manufacturing ecosystem in Brainport Eindhoven,” added Ilse Massart, Senior Investment Manager at Brabant Development Agency (BOM). “We are pleased to be able to contribute to AM-Flow’s ambitious growth plans and to assist the management team in the international expansion.”
End-to-end automation and 3D printing
Automating the 3D printing process is viewed by many within the industry as vital to making it a cost-effective alternative to conventional manufacturing technologies. As a result, a number of software companies have developed advanced analytical programs in recent years, which offer to manage the production workflow in full, from start to finish.
Sintavia has collaborated with Siemens Digital Industries Software to develop an end-to-end additive manufacturing software solution as part of Siemens’ Xcelerator portfolio. The three-year agreement signed by the firms will see Sintavia provide Siemens with testing and technical feedback on a beta version of the program.
German 3D printer OEM EOS adopted UK software company AMFG’s MES program to improve streaming and connectivity between its machines in November 2019. AMFG’s plaform provided EOS with direct machine control during operation, and enabled the end-to-end workflow automation of its 3D printers.
Workflow software developer Authentise meanwhile, has partnered with Addiguru, a developer of in-situ process monitoring systems, to advance its proprietary AMES program. The duo aim to integrate computer vision and AI-based monitoring functionality into the software, allowing for real-time intervention within the production process.
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Featured image shows a selection of 3D printed parts undergoing shape identification via AM-Flow’s AM-VISION software. Photo via AM-Flow.
