Metal AM Autumn 2019 by Inovar Communications

Towards a digital twin for AM

event was sponsored by software vendors for ThingWorx, Solvia, Simufact, Materialise and Flow-3D, emphasising the interest from the commercial software community. The specific aims of the symposium were to define the requirements for a true digital twin of AM, identify the main barriers to developing such software models, discuss potential solutions to overcome those barriers and plan a roadmap that can provide general guidance for the development of digital twins. These aims were achieved through a combination of keynote lectures, poster presentations and facilitated discussion sessions. Keynotes were spread between modelling, experimental validation and machine learning/artificial intelligence for model speed-up purposes. Some of the main messages from the symposium’s keynote speakers are outlined below. These were the opinions of the speakers, and some may not necessarily be incorporated in the creation of the roadmap. The use of digital twins in tailoring metal AM processes The overarching theme of the presentation by Dr Ibo Matthews, Lawrence Livermore National Laboratory (LLNL), USA, was the potential that exists for the use of digital twins in tailoring metal AM processes. A sound understanding of the physics involved, as well as the availability of suitable experimental data for validation purposes, were emphasised as prerequisites for accurate modelling. The following phenomena were among those listed as needing further in-depth understanding: • Liquid spatter due to unstable local laser/melt-pool/powder bed interactions • Depressions in the powder bed due to vapour pressure and pore formation as a result of the highly dynamic interactions and the resulting flow profiles and subsequent solidification • The effect of all of the above and cooling rates on microstructure evolution.

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LLNL is presently studying the use of machine learning (ML) to predict process fidelity (via track width) based on in-situ high-speed video monitoring, but these methods will be later augmented by sophisticated algorithms that can accelerate part certification. Fundamental physics relating to powder-bed technology and complexity in materials The main discussion points from the presentation by Prof Leila Ladani, University of Texas at Arlington, USA, focused on the fundamental physics relating to powder bed technology and complexity in materials. The essential take-aways from this presentation were as follows: • The physics associated with the various phenomena and materials are too complex to be modelled in a computationally efficient way, hence it is advisable to identify a few parameters that have the most influence and concentrate on modelling those influences using suitable simplifications and assumptions, at least for a start (for instance, consider modelling the powder bed as a block rather than as a collection of particles using ‘effective powder thermal conductivity’) • It is critical to have accurate thermophysical properties, which may be temperature- and/or laser wavelength-dependent • The research community needs more innovative approaches to be able to model the processes with the lowest computational costs. Modelling should go hand-in-glove with experimental efforts In the presentation by Prof Tarasankar DebRoy, Pennsylvania State University, USA, compelling justification was provided for using modelling hand-in-glove with experimental efforts for expanding the knowledge base associated with metal AM processes. DebRoy mentioned that it took the welding community close to a century to develop the knowhow that they currently possess. If we

Metal Additive Manufacturing | Autumn/Fall 2019

extrapolated that to the AM process, where the number of permutations and combinations in terms of process parameters easily surpasses that of welding, and which is slower and more expensive, it would take much longer to reach that level of knowledge – unless it is done differently. Difficulties in optimising microstructures, part properties, and control of distortion after a build were listed as key challenges that can be tackled using digital twins. The speaker mentioned that other benefits of using digital twins included: • A shortened time for bringing a product to market • Increased chances for introducing process and product design innovations in the industry • Improved agility to successfully follow market trends and the creation of a process-savvy workforce. Some of the sub-models that can become the building blocks of a digital twin for metal AM processes were considered, and some hurdles in their development were outlined. These include the lack of a coordinated global approach between the stakeholders who are driven by their own agendas, the unwillingness of large multinational corporations to share knowledge and the difficulty in synthesising the huge amount of data being generated in the field. Enabling weight reductions in parts The main thrust of the presentation by Prof Dongdong Gu, Nanjing University of Aeronautics and Astronautics, China, was to bring to the attention of the delegates the importance of the metal AM industry to aeronautics and space in terms of enabling weight reductions in parts (through the design freedom it affords) and the acute need to develop more suitable materials and novel process innovations to achieve this purpose. Again, the requirement for an in-depth understanding of the science underlying various processes was emphasised, with particular references to particle flow, laser energy

Vol. 5 No. 3