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]
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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.
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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.
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There is no shortage of Additive Manufacturing machines humming away in research laboratories, producing test pieces and exhibits for trade shows, but the hard truth is that relatively few are making components for serial production. In part, this is because the world is still waiting for materials which enable the technology to fulfil its true potential. In this article, Rebecca Gingell and colleagues from OxMet Technologies, Oxford, UK, explain how the company is approaching the design of novel alloys for AM, and reflect on its progress so far. [First published in Metal AM Vol. 5 No. 4, Winter 2019]
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Terms such as Industry 4.0, the Digital Thread and the Digital Twin have become familiar buzzwords in manufacturing, but many such terms barely make sense to IT experts, let alone AM professionals. In the crowded and jargon-heavy landscape of solutions for digitalisation, articulating future AM software trends can help offer clarity and confidence in IT investments and give insight into the data-driven future of manufacturing, believes Authentise’s Andre Wegner, who shares his vision of the route to developing an effective digital factory with Metal AM’s Emily-Jo Hopson. [First published in Metal AM Vol. 5 No. 2, Summer 2019]
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Additive Manufacturing is not a cheap production process. The software, machine time, materials and expertise required to make the most of the technology all come at a significant cost. The resulting financial pressures may give rise to the temptation to select a material on its price and view advanced topology optimisation as a luxury. As Jon Meyer, APWORKS, and John Barnes, The Barnes Group Advisors, demonstrate, the unique capabilities of AM mean that basing material choice on cost without considering the impact of material performance on the mass of the part is a false economy, limiting the competitiveness of AM and the potential of an application [First published in Metal AM Vol. 5 No. 1, Spring 2019]
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In a bid to better understand the impact of process parameters on material performance, the U.S. Navy turned to Senvol to develop data-driven machine learning software for Additive Manufacturing. As Zach Simkin and Annie Wang explain, such an approach allows the user to overcome the time and expense required by a conventional trial-and-error process, whilst delivering remarkably accurate results that have the potential to accelerate application development [First published in Metal AM Vol. 5 No. 1, Spring 2019]
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X-ray Computed Tomography (CT), also widely known as MicroCT, is a proven method for not only checking the structural integrity of additively manufactured (AM) parts – for example for unwanted porosity – but also for checking a build’s dimensional accuracy. The main advantage of the technique is of course the non-destructive nature of the assessment; however, there are also many misunderstandings about the capabilities and complexity of the technology. Prof Anton du Plessis and Dr Jess M Waller review the application of CT testing in relation to metal AM and highlight the advantages of a move towards standardised test methods [First published in Metal AM Vol. 4 No. 4, Winter 2018]
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As one of the world’s largest industrial companies, Siemens has experienced first hand the process of taking metal AM from the R&D laboratory to the series production of critical components for its power generation business. Today, it is supporting the global industrialisation of the technology through its Siemens NX Additive Manufacturing software. In the following report the company’s Aaron Frankel and Ashley Eckhoff explain their belief that, whilst the potential of AM is massive, digitalisation will play a critical role in enabling its transition from a prototyping tool to a serial production technology [First published in Metal AM Vol. 4 No. 3, Autumn 2018]
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In July 2018, Metal Additive Manufacturing magazine’s Emily-Jo Hopson attended the company’s exclusive EOS Technology Days for an advance preview of its new metal Additive Manufacturing system, the EOS M 300, and a look at its vision for AM and the technology’s place in the digital factory of the future. Held at the company’s attractive rural headquarters in Krailling, Germany, the event offered attendees insight into areas that are key to EOS’s current development strategy [First published in Metal AM Vol. 4 No. 3, Autumn 2018]
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Over the past few years, metal Additive Manufacturing has received a lot of attention, and with good reason: the technology has the potential to radically alter the design and production of components and products in many industries. Yet in spite of the excitement that surrounds AM, the prospect of wider industrial adoption continues to face significant challenges. Ansys Inc’s Dave Conover explains how simulation, traditionally the domain of product design instead of manufacturing, has swiftly gained recognition as a key technology which can be used to ease the transition from conventional to Additive Manufacturing [First published in Metal AM Vol. 4 No. 3, Autumn 2018]
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Designing a component for AM whilst taking advantage of all the opportunities that the technology presents can result in many variables. Even a group of experienced Design for Additive Manufacturing (DfAM) experts will end up with significantly different build strategies for an identical part. In the following article, Olaf Diegel and Terry Wohlers consider how software innovations could further streamline the AM process, from part positioning and stress management to surface finish considerations and quality control
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