---
title: "AM-Flow raises $4M to deliver full end-to-end AM automation"
url: https://www.voxelmatters.com/additive-maufacturing-automation/
date: 2020-10-15
modified: 2020-10-16
lang: en
author: "Adam Strömbergsson"
description: "AM-Flow, a Dutch industrial automation company focused on additive manufacturing automation, obtained four million dollars of Series A funding, which allows the company to begin providing step-change automation to the..."
categories:
  - "Acquisitions, Mergers & Partnerships"
  - "Automation"
tags:
  - "insights"
image: https://www.voxelmatters.com/wp-content/uploads/2020/10/01-Home-ipad-V3-640x329.png
word_count: 438
---

# AM-Flow raises $4M to deliver full end-to-end AM automation

[AM-Flow](https://www.3dprintingbusiness.directory/company/am-flow/), a Dutch industrial automation company focused on additive manufacturing automation, obtained four million dollars of Series A funding, which allows the company to begin providing step-change automation to the AM industry. The funding also allows the company to move toward its industry 4.0 goal of the lights-out factory, where artificial intelligence computer vision, motion and robotics process 3D-printed parts. AM-Flow’s commitment to supplying this intelligence and accompanying robotics will enhance manufacturing speeds and efficiency levels.

The impact of AM-Flow’s developing technology is that companies will be able to prevent cost-driven offshoring. AM’s strength in local operations means that companies can refocus their operations right beside consumer groups while maintaining low labor and start-up costs.

This value proposition attracted several early investors. [BOM Brabant Venture](https://www.bom.nl/brabant-ventures) led the series-A funding round with support from [Materialise](https://www.3dprintingbusiness.directory/company/materialise/), [Midwest Prototyping](https://www.3dprintingbusiness.directory/company/midwest-prototyping/) and [Innovatiefonds Noord-Holland](https://innovatiefondsnoordholland.nl/en/home-2/). Existing investors Miller Turner and [DOEN Participaties](https://www.doen.nl/doen-participaties-en/about.htm) also contributed.

Engineering 3D-printing production lines is challenging because each line has to process 3D-printed parts with an infinite variety of geometries. This variety poses difficulties in identification, sorting, quality control, handling, transporting and packaging automated additive manufacturing. AM-Flow applies machine learning and an Industry 4.0 approach from the ground-up, which allows the company to deliver modular solutions.

![The company](https://www.voxelmatters.com//wp-content/uploads/2020/10/AM-VISION-1320x669-1-1-e1602782757589-338x340.png)The company's AM Vision machine used to identify 3D-printed parts

AM-Flow’s CEO, Stefan Rink, welcomed the new investors. He pointed up their leadership in the AM space: “We are delighted to welcome our new investors, and I would like to thank our existing shareholders for their continued support. This strong syndicate of high-tech investors validates our approach and the funding enables us to expand our solution portfolio and market presence.”

This leadership in a twelve-billion-dollar industry is based on pulling innovative companies up as the industry consolidates. AM’s utility has been on display through the current COVID-19 pandemic. It has more broadly been heralded as a way to decouple mass production from global supply chains. This paradigm shift reduces greenhouse gas emissions by reducing international shipping. Mr. Rink’s comments about AM-Flow’s team show the company working with AM’s promise in mind: “We have a team that is passionate about enabling Additive Manufacturing to live up to its sustainability promise: local, distributed manufacturing. To drive further adoption of Additive Manufacturing, the industry must get to competitive price and quality levels per part and shift her focus from the 3D-printer to the AM Factory.”

The additive manufacturing automation that AM-Flow is currently developing allows industries to shift resources away from traditional manufacturing models toward remote-supervised production facilities. This move can increase production efficiency; it also allows workshop-like manufacturing at scale in localities.