LPW Technology—a UK-based manufacturer of metal additive manufacturing (AM) powders—has been granted the LPW/Royal Academy of Engineering Research Chair at Lancaster University, a post dedicated to alloy data mining and microstructure design for the development of high-performance AM alloy powders.
Professor Pedro Rivera has been appointed as the LPW/Royal Academy of Engineering Research Chair. He is transferring from his post as assistant director of research at SKF University Technology Centre, Cambridge University, that has seen him focus on sophisticated modeling for the generation of new alloys.
As the LPW/Royal Academy of Engineering Research Chair, Professor Rivera is to lead research into the engineering of high-performance AM alloy powders based on thermodynamic and kinetic modeling and neural networking and genetic algorithms. He will oversee the creation of statistical models that take account of powder size, composition and atmospheric conditions as well as component properties such as strength, ductility, hardness and corrosion, allowing for the realization of robust processing parameters for industrial AM.
An understanding of how powder composition affects the end material structure is expected to pave the way for designing and creating components that feature localized properties. This capability could open up significant opportunities in critical industries, for example, components for aircraft where the exterior needs to be hard and the interior lightweight and prosthetic joints where the exterior needs to be biocompatible and the interior low density.
LPW Technology is assembling a team of researchers at LPW Technology and Lancaster University that will work together to develop the new alloy powders. The company’s PowderLab will perform full characterizations of the powders and material testing following component builds on its in-house metal AM machines.
LPW Technology’s PowderSolve metal AM powder traceability software is described as ‘the backbone of the research project’ and will be relied on to ensure that maximum intelligence in powder performance is mined from the vast array of inputs. The research team will use the software to collate, simulate, record and analyze data throughout the AM build process, relating it directly to component functionality. Ultimately, the company envisions PowderSolve enabling companies to use AM build process data to develop and optimize their own AM powders and processes.
Professor 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.’