New LPW / Royal Academy of Engineering Research Chair created to mine, process and alloy data, and to model novel alloys for optimising the additive manufacturing process.

15 Aug, 2017

The LPW/Royal Academy of Engineering Research Chair in ‘Alloy and microstructure design for additive layer manufacturing’ has been created to capitalise on the exciting potential data mining and alloy design for the rapidly growing metal additive manufacturing (AM) technology for novel, high-performance metal powder development.

Industrialisation of metal additive manufacturing is at the point of delivering vast quantities of data from the complex metallurgical processes involved in creating components through metal AM. As this technology is poised to disrupt the established techniques for fabricating metal components so collecting data, and simulating new compositions and microstructures, promises to transform the approach to generating novel high-performance alloys for applications in critical industries.

Professor Pedro Rivera has been appointed to the LPW / Royal Academy of Engineering Chair at Lancaster University. Professor Rivera is transferring from his post as Assistant Director of Research, SKF University Technology Centre, Cambridge University where his focus has been on sophisticated modelling to generate new alloys. His appointment to the new research chair at Lancaster University will see research into engineering new materials harness the power of thermodynamic and kinetic modelling, combined with the concept of neural networking and genetic algorithms to design revolutionary high-performance AM specific alloys.

Professor Pedro Rivera commented “AM offers incredible design freedom to manufacture parts unable to be created by such established methods as forging and casting. Conventional alloys used for AM can be extremely sensitive to parameters such as oxygen content where the variation is intrinsic to the AM process. This research will create truly novel metal powders by controlling the microstructures and compositions so critical for high performing AM-specific alloys.”

 By developing statistical models that take account of powder size, composition and atmospheric conditions with component properties such as strength, ductility, hardness and corrosion, robust processing parameters can be developed to realise AM on an industrial scale.

As Dr Phil Carroll explained, “In understanding how metal powder composition can affect the end material microstructure we can begin to design and create parts where the composition across the component varies. The opportunity to design localised properties in a single part opens up tremendous possibilities. Imagine high temperature aerospace parts where the exterior is hard whilst the interior is lightweight, prosthetic joints delivering surface biocompatibility with low density interiors.”

 Industrial partner, LPW Technology Ltd, is committing to a team of researchers at LPW and Lancaster University working together in the pursuit of developing new AM specific alloys. To prove material functionality, LPW will make available its world-class AM PowderLab to undertake full characterisation of the metal powder alloys, material testing following component builds on its in-house metal AM machines.

LPW’s PowderSolve AM traceability software tool will be the backbone of this data-rich research project, to ensure that the maximum intelligence in powder performance is mined from the vast array of inputs. This will enable collation of material, test and build data from complex simulation and material analysis, to proof of alloy performance. Ultimately through PowderSolve, LPW aims to enable companies to use AM process data to develop and optimise their own AM materials and processes.

The ability to collect, simulate, record and analyse data throughout the AM build process and relate accurately to component functionality, underpins the application of fundamental science to practical industrial adoption. PowderSolve is key to controlling this data and this research promises to add confidence in the intelligence and control of additive manufacturing, accelerating high-growth in critical production environments including the aerospace and medical sectors.

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