Software

A game of hide and seek with Renishaw and Altair: Artificial Intelligence-powered quality assurance on the fly

Is it possible to actively monitor the huge volumes of data from a Laser Beam Powder Bed Fusion (PBF-LB) machine to identify, through machine learning (ML), build errors as they happen? To answer this question, Renishaw and Altair played a unique game of hide and seek. In this innovative experiment, an error was deliberately hidden in a build for an artificial intelligence (AI)-based solution to find. The hope? True ‘on the fly’ quality assurance for Additive Manufacturing processes for accelerated product development, and dramatically reduced post-production quality checks. [First published in Metal AM Vol. 8 No. 1, Spring 2022] ... Read more »

Laser Beam Powder Bed Fusion: Process developments and numerical simulation

A technical session at the Euro PM2021 Virtual Congress, organised by the European Powder Metallurgy Association (EPMA) and held October 18–22, 2021, was devoted to the consideration of process developments and numerical simulation approaches for Powder Bed Fusion (PBF) Additive Manufacturing technologies. In this report, Dr David Whittaker reviews four of the papers presented on this topic, looking at process parameter optimisation, increasing quality for Ti6Al4V medical parts, techniques to improve the AM of hot-work tool steels, and powder spreading improvements for stainless steel. [First published in Metal AM Vol. 7 No. 4, Winter 2021] ... Read more »

The inestimable value of AI: How Machine Learning can help AM project teams achieve their goals and beyond

They each have similar two-letter acronyms, and, for both technologies, it can be hard to separate hype from reality. But Artificial Intelligence (AI) and Additive Manufacturing also overlap in interesting and beneficial ways. In this article, Stephen Warde of Intellegens considers how AI methods such as Machine Learning (ML) could help AM to deliver against expectations – and at the very least, to meet more realistic and commercially essential objectives, such as consistently delivering lighter, stronger components and supporting on-demand manufacturing. [First published in Metal AM Vol. 7 No. 4, Winter 2021] ... Read more »

Strategies for advancing the automation of metal Additive Manufacturing

In the early days of metal Additive Manufacturing process development, automation was off the radar of machine manufacturers. Technologies created for rapid prototyping simply had no need for it and, until the last decade, few truly anticipated the pace at which Laser Beam Powder Bed Fusion and Binder Jetting have evolved in the race towards the series production of metal parts. In this article, Joseph Kowen reports on how the industry has addressed the challenges of automation so far, and what developments we can expect in the near future. [First published in Metal AM Vol. 6 No. 4, Winter 2020] ... Read more »

Metal AM magazine Summer 2022

Machine Learning and Additive Manufacturing: What does the future hold?

As industry marches toward automation, networked communication and robotics, Additive Manufacturing has a unique advantage. No other production technology has been designed, from its inception, to enable connectivity and communication; AM machines around the world are already producing more build data than any other manufacturing technology. If used properly, this data will provide the foundation for the development of Machine Learning tools that can improve and industrialise the AM process at nearly every point in the workflow. In this article, Chelsea Cummings and John Barnes, from The Barnes Global Advisors, discuss the present and future of Machine Learning in AM. [First published in Metal AM Vol. 6 No. 4, Winter 2020] ... Read more »

Metal AM magazine Summer 2022

CFD simulation for metal Additive Manufacturing: Applications in laser- and sinter-based processes

Computational Fluid Dynamics (CFD) is widely applied to solve a broad range of research and engineering problems, from aerodynamics to engine combustion and microfluidics. In this article, Pareekshith Allu, Senior CFD Engineer at Flow Science, Inc, explains how CFD can also be used to improve laser- and non-laser-based metal Additive Manufacturing processes, including Laser Beam Powder Bed Fusion (PBF-LB), Directed Energy Deposition (DED), Binder Jetting (BJT) and Material Extrusion (MEX). [First published in Metal AM Vol. 6 No. 4, Winter 2020] ... Read more »

Metal AM magazine Summer 2022

Link3D’s ‘Additive Manufacturing Maturity Model’: Developing an agile and resilient supply chain

As the metal Additive Manufacturing industry matures at a rapid rate, organisations are now faced with the challenge of scaling their AM operations. Based on a study of 253 companies in a number of sectors, US-based AM software specialist Link3D has developed an ‘Additive Manufacturing Maturity Model’. This simple model can be used as a tool to understand an organisation’s AM maturity whilst also helping them navigate the steps to developing an agile and resilient AM supply chain. Shane Fox, CEO and co-founder of Link3D, explains. [First published in Metal AM Vol. 6 No. 2, Summer 2020] ... Read more »

Mass-production using PBF-LB: How laser beam measurements can help pave the way

Laser Beam Powder Bed Fusion (PBF-LB) is a technology rich in process parameters and exacting material specifications, all developed with the aim of delivery quality and repeatability as the industry moves towards volume production. However, without control of a laser’s focal spot, neither the material specification nor the handling of the material in the build chamber can guarantee the hoped-for results. As Ophir Spiricon Europe’s Christian Dini explains, when it comes to lasers, there is no control without the gathering of reliable data. [First published in Metal AM Vol. 6 No. 2, Summer 2020] ... Read more »

Towards a true digital twin for the metal Additive Manufacturing process

On July 4, 2019, Australia’s Commonwealth Scientific and Industrial Research Organisation (CSIRO) sponsored and co-organised a one-day symposium in Melbourne entitled ‘Towards a True Digital Twin’. The event, which followed APICAM 2019, the 2nd Asia-Pacific International Conference on Additive Manufacturing, brought together experts in a range of relevant fields including metal Additive Manufacturing, computational modelling, multi-scale techniques, structure-property relations, machine learning and artificial intelligence, and digital twins of industrial processes. Here, CSIRO Manufacturing’s Dr Dayalan Gunasegaram and Dr Tony Murphy consider the importance of the digital twin in AM and report on some of the event’s key findings. ... Read more »

Fig. 1 How digital twins add value to a business

Evaluation of Sigma Labs’ in-situ process control system during Additive Manufacturing

As Additive Manufacturing shifts from process development and characterisation activities into the series production of components for critical applications, in-process quality control, qualification and certification are areas of fundamental importance to widespread adoption of AM [1,2]. In the following report, engineers from Sigma Labs, Inc., present the results of a study to establish a correlation between in-process data collected using the company’s PrintRite3D SENSORPAK® system and PrintRite3D INSPECT® software and the results of the metallographic testing of as-built specimens. ... Read more »

Fig. 1 CAD Image of the build configuration. The PCS cylinder is marked as specimen 2. Individual parametric build segments are numbered 1 to 11 starting directly against the build plate

In the latest issue of Metal AM magazine

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Extensive AM industry news coverage, as well as the following exclusive deep-dive articles:

  • Transforming access to medical implants with PrinterPrezz
  • Lessons from 2021’s Olympic bike crash
  • Xerox liquid metal AM
  • Additive Manufacturing for oil, gas and maritime
  • Multi-material metal parts by Powder Bed Fusion
  • Findings from Wohlers Report 2022
  • The challenge of grain size: X-ray powder diffraction analysis of parts made by metal AM

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